Program for 2014 IEEE Workshop on Statistical Signal Processing (SSP)

Time Grand Hall Interactive Session Room 1 Room 2 Session

Sunday, June 29

10:00 am-01:00 pm     Tut 1: Point Process, Random Finite Sets and Multi-Object Estimation (Ba-Ngu Vo) Tut 2: Cyclostationary Signal Processing and its Generalizations (Antonio Napolitano)  
02:00 pm-05:00 pm     Tut 3: Compressive Parameter Estimation: The Good, The Bad, and The Ugly (Yuejie Chi & Ali Pezeshki) Tut 4: Harmonic Analysis on and of Irregular Domains, Graphs, and Networks (Naoki Saito)  
06:00 pm-07:00 pm         Welcoming Reception

Monday, June 30

08:30 am-08:45 am Opening Presentation        
08:45 am-09:45 am S1: Plenary Lecture I: Recent Results in Modelling National Economic Time Series Data (Brian D. O. Anderson)        
09:45 am-10:15 am         Morning Tea
10:15 am-12:15 pm   MM01: Random matrix and advances in signal processing,
MM02: Signal processing applications,
MM03: Adaptive systems and signal processing I,
MM04: Biomedical signal processing I,
MM05: Detection and estimation theory I
     
12:15 pm-01:30 pm         Lunch
01:30 pm-02:30 pm S2: Plenary Lecture 2: Particle Methods for Inference in Non-Linear Non-Gaussian State-Space Models (Arnaud Doucet)        
02:30 pm-03:00 pm         Afternoon Tea
03:00 pm-05:00 pm   MA01: Recent advances in Monte Carlo methods in statistical signal and image processing,
MA02: Learning theory and pattern recognition I,
MA03: Adaptive systems and signal processing II,
MA04: Biomedical signal processing II,
MA05: Detection and estimation theory II
     

Tuesday, July 1

08:30 am-09:30 am S3: Plenary Lecture III: Coherence as an Organizing Principle in Signal Processing (Louis Scharf)        
09:30 am-10:00 am         Morning Tea
10:00 am-12:00 pm   TM01: Stochastic Geometry in Signal Processing,
TM02: Learning theory and pattern recognition II,
TM03: Monte Carlo methods I,
TM04: Compressed Sensing I,
TM05: Detection and estimation theory III
     
12:00 pm-01:30 pm         Lunch
01:30 pm-02:30 pm S4: Plenary Lecture IV: Sparse stochastic processes, matched wavelet expansions and ICA (Michael Unser)        
02:30 pm-03:00 pm         Afternoon Tea
03:00 pm-05:00 pm   TA01: Advances in robust statistical signal processing I,
TA02: Array processing, radar and sonar,
TA03: Monte Carlo methods II,
TA04: Compressed sensing II,
TA05: Communication systems and networks I
     
07:00 pm-09:00 pm Conference Dinner        

Wednesday, July 2

08:30 am-09:30 am S5: Plenary Lecture V: The Square Kilometre Array: new paradigms required for signal processing in astronomy (Steven Tingay)        
09:30 am-10:30 am S6: Plenary Lecture VI: Enabling Functional Neuro-imaging with Statistical Signal Processing (Victor Solo)        
10:30 am-11:00 am         Morning Tea
11:00 am-01:00 pm   WM01: Advances in robust statistical signal processing II,
WM02: Radar Processing,
WM03: Adaptive systems and signal processing III,
WM04: Learning theory and pattern recognition III,
WM05: Communication systems and networks II,
WM06: System identification and calibration
     
01:00 pm-02:30 pm         Lunch

Sunday, June 29

Sunday, June 29, 10:00 - 13:00

Tut 1: Point Process, Random Finite Sets and Multi-Object Estimation (Ba-Ngu Vo)go to top

Ba-Ngu Vo
Room 1

Multi-object systems are systems in which the number of objects and their states are unknown and stochastically vary with time. Multi-object systems arise in a host of applications areas, including aerospace, defense, computer vision, robotic and biomedical research. The last decade has witnessed exciting developments in multi-object state estimation with the introduction of random finite set to the field. The history of random set traces back to the problem of Buffon's needle and has long been used by statisticians in many diverse applications including astronomy, atomic physics, biology, sampling theory, stereology, etc. Since 2003, Mahler's seminal work on the random finite set approach to multi-object system, which culminated in the probability hypothesis density (PHD) filter, has continued to attract substantial interests from academia and industry alike.

This tutorial is an introduction to the random finite set paradigm to dynamic state estimation and outlines recent developments beyond the PHD filters. The session will present participants with the latest advances in multi-object dynamic state estimation methodology. It provides a unified perspective of multi-object filtering in a very intuitive manner by drawing direct parallels with the simpler problem of single-object filtering. Random finite sets are used as a tool for modeling multi-object systems and formulating the multi-object estimation problem in the Bayesian framework. Latest state-of-the-arts algorithms, including the PHD filters are presented. These techniques are illustrated in a number of applications areas including, radar/sonar, computer vision, and robotics. It is envisaged that participants will come away with sufficient know-how to apply these algorithms.

Dynamic state estimation is a significant component of statistical signal processing. This tutor presents important theoretical and algorithmic advances in dynamic multi-object estimation. This is an emerging area of research in statistical signal processing with a wide range of applications, which will enrich the statistical signal processing literature.

Tut 2: Cyclostationary Signal Processing and its Generalizations (Antonio Napolitano)go to top

Antonio Napolitano
Room 2

In this tutorial, a review of cyclostationarity-based signal processing techniques for weak-signal detection, source location, and modulation classification will be presented [1]. Application to radar/sonar and cognitive radio will be considered. New classes of processes that generalize the cyclostationary model will be also reviewed [4], [5]. For these classes, the basic problems of probabilistic characterization, statistical function estimation, and sampling will be addressed [2], [3], [4], [5]. It will be shown how the new models allow one to remove constraints imposed by the so-called narrow-band condition [4, Sec. 7.5.1] which is necessary for cyclostationarity-based algorithms. With respect to cyclostationarity-based algorithms, the new models will allow one to consider scenarios with wider bandwidths, larger relative radial speeds between transmitter and receiver, larger data-record lengths, and lower values of SNR and SIR [5]. Cyclostationary signal processing, cognitive radio and radar, and wide-band mobile communications are hot topics for the signal processing community. A tutorial on consolidated and emerging results in these topics is of interest for attendees of SSP 2014.

Sunday, June 29, 14:00 - 17:00

Tut 3: Compressive Parameter Estimation: The Good, The Bad, and The Ugly (Yuejie Chi & Ali Pezeshki)go to top

Yuejie Chi & Ali Pezeshki
Room 1

In a great number of sensing and imaging applications, we are interested in resolving a sparse superposition of parameterized signals from noisy measurements collected at a sensor suite, and the unknown signal parameters typically lie in a continuous space. Compressed sensing has been recently recognized as an emerging tool to take advantage of the sparsity prior to discretizing the continuous parameter space into a fine grid; this, however, raises both theoretical and algorithmic issues. This tutorial will examine the history of parameter estimation algorithms, give a survey of compressed sensing, and discuss both benefits and drawbacks of compressed sensing approaches for parameter estimation. The tutorial will examine sensitivities of compressed sensing to model mismatch and gridding of the parameter space and will discuss the impact of compressive sensing on Fisher information and threshold effects in parameter estimation. It will also cover recently proposed convex optimization methods that aim to eliminate gridding issues while maintaining some of the benefits of compressed sensing.

Tut 4: Harmonic Analysis on and of Irregular Domains, Graphs, and Networks (Naoki Saito)go to top

Naoki Saito
Room 2

Traditional harmonic analytic tools such as Fourier and wavelet transforms have been the ‘crown jewels' for a variety of fields involving regularly-sampled data such as data compression, image analysis, and statistical signal processing. On the other hand, there is an explosion of interest and demand to analyze data sampled on irregular grids, graphs, and networks, e.g., biological networks, sensor networks, social networks, etc. The conventional harmonic analysis tools originally developed for regular Euclidean spaces and regular lattices cannot directly handle such datasets. They are now being transferred to these more general settings to analyze data measured on them as well as their geometric and topological structures. In this process, the eigenvalues and eigenfunctions of the Laplace operator appropriately defined on those domains play a pivotal role. This can be easily recognized since the sine and cosine functions are the Laplacian eigenfunctions for the unit interval in R (with appropriate boundary conditions) after all. Together with the corresponding eigenvalues, the Laplacian eigenfunctions carry important topological and geometric information of the domains where the data are sampled. Moreover, they provide useful information to partition the domains into subdomains via the celebrated Courant nodal domain theorem, and hence serve as building blocks for constructing wavelet-like multiscale basis functions on such domains. In this tutorial, I plan to review this emerging field from the basics to cutting-edge applications, which I strongly believe will benefit the participants of this SSP workshop. The topics covered in this tutorial are: 1) Motivations; 2) Basics of Laplacian eigenvalue problems; 3) Laplacian eigenvalue problems on irregular domains; spectral geometry; 4) Laplacian eigenvalue problems on graphs and networks; building wavelet-like bases on graphs and networks; 5) Applications in signal processing on graphs and networks.

Sunday, June 29, 18:00 - 19:00

Welcoming Receptiongo to top

Monday, June 30

Monday, June 30, 08:30 - 08:45

Opening Presentationgo to top

Room: Grand Hall

Monday, June 30, 08:45 - 09:45

S1: Plenary Lecture I: Recent Results in Modelling National Economic Time Series Data (Brian D. O. Anderson)go to top

Brian D. O. Anderson, The Australian National University and National ICT Australia
Room: Grand Hall

Statistics offices in most advanced countries collect large numbers of economic time series—over 300 individual series is a typical number. Such series are, among other purposes, used for building models of a nation's economy, for use by agencies like central banks. The latter bodies are interested in short to medium term forecasting, and formulate policy in the light of those forecasts.

The task of model building is challenging, and has been addressed in recent years. The favoured classes of models is known as Generalized Dynamic Factor Models, and take the form of a linear discrete-time system excited by vector white noise, with the vector of measured series corresponding to the model's vector output. The input vector dimension and state dimension of virtually always much less than the output vector dimension. A major, but not yet fully resolved challenge is to handle the fact that the various economic time series are not all collected with the same period; most commonly, some series are available monthly and others quarterly. This fact complicates substantially the task of model building.

This talk will review recent progress in the area, including the major conclusion that there is generically no loss of generality in working with autoregressive models, and that with mixed frequency data, under reasonable assumptions a high frequency (monthly period) state-variable model can be constructed, the outputs of which are formed from the states at the two different sampling periods.

Monday, June 30, 09:45 - 10:15

Morning Teago to top

Monday, June 30, 10:15 - 12:15

MM01: Random matrix and advances in signal processinggo to top

Chair: Romain Couillet (Special Session)
Room: Interactive Session
Robust M-estimator of scatter for large elliptical samples
Romain Couillet and Frederic Pascal (CentraleSupélec, France)
Discovering Statistical Vulnerabilities in Highly Mutable Viruses: A Random Matrix Approach
Ahmed A. Quadeer (The Hong Kong University of Science & Technology, Hong Kong); Raymond Hall Yip Louie (Hong Kong University of Science and Technology, Hong Kong); Karthik Shekhar (MIT, USA); Arup Chakraborty (Massachusetts Institute of Technology, USA); I-Ming Hsing and Matthew R McKay (Hong Kong University of Science and Technology, Hong Kong)
Regularized Block Toeplitz Covariance Matrix Estimation via Kronecker Product Expansions
Kristjan Greenewald and Alfred Hero III (University of Michigan, USA)
Improved Robust PCA using low-rank denoising with optimal singular value shrinkage
Brian E Moore, Raj Rao Nadakuditi and Jeff Fessler (University of Michigan, USA)
On estimation of the noise variance in a high dimensional signal detection model
Damien Passemier (The Hong Kong University of Science and Technology, Hong Kong); Jeff J. Yao (The University of Hong Kong, Hong Kong)

MM02: Signal processing applicationsgo to top

Chair: David Infield
Room: Interactive Session
Food Steganography with Olfactory White
Kush Varshney (IBM Thomas J. Watson Research Center, USA); Lav R. Varshney (University of Illinois at Urbana-Champaign, USA)
Active Odor Cancellation
Kush Varshney (IBM Thomas J. Watson Research Center, USA); Lav R. Varshney (University of Illinois at Urbana-Champaign, USA)
A Widely Linear Multichannel Wiener Filter for Wind Prediction
Jethro Dowell, Stephan Weiss and David Infield (University of Strathclyde, United Kingdom (Great Britain)); Swati Chandna (University of Surrey, United Kingdom (Great Britain))
Variational Bayesian model averaging for audio source separation
Xabier Jaureguiberry (Institut Mines-Télécom, Télécom ParisTech, CNRS LTCI, France); Emmanuel Vincent (Inria Nancy - Grand Est, France); Gaël Richard (Institut Mines-Télécom, Télécom ParisTech, CNRS-LTCI, France)
Feeder-Level Fault Detection and Classification with Multiple Sensors: A Smart Grid Scenario
Nan Wang and Visvakumar Aravinthan (Wichita State University, USA); Yanwu Ding (Wichita state university, USA)

MM03: Adaptive systems and signal processing Igo to top

Chair: Akramus Salehin
Room: Interactive Session
Adaptive Multi-Resolution Windowing Technique for Localized Spatio-Spectral Analysis
Zubair Khalid (Australian National University, Australia); Rodney Andrew Kennedy, Salman Durrani and Parastoo Sadeghi (The Australian National University, Australia)
Analysis of Degrees of Freedom of Wideband Random Multipath Fields Observed Over Time and Space Windows
Farhana Bashar, S. M. Akramus Salehin and Thushara D. Abhayapala (Australian National University, Australia)
EM Algorithm for Estimating Poisson Measurement Noise
Garry A. Einicke (CSIRO, Australia)
A Signal Disambiguation Algorithm for use in Multi-Beam Receivers
Jeremy Stringer, Geoffrey Akers and Gary Lamont (Air Force Institute of Technology, USA)
Multichannel Wiener Filter Estimation using Source Location Knowledge for Speech Enhancement
Craig Anderson (Victoria University, New Zealand); Paul D Teal (Victoria University of Wellington, New Zealand); Mark Poletti (Callaghan Innovation, New Zealand)

MM04: Biomedical signal processing Igo to top

Chair: Mohamed Deriche
Room: Interactive Session
Social Signal Processing for Pain Monitoring Using a Hidden Conditional Random Field
Afsaneh Ghasemi Ghaleh Bahmani and Xinyu Wei (Queensland University of Technology, Australia); Patrick Lucey (Disney Research, Pittsburgh, USA); Sridha Sridharan and Clinton Fookes (Queensland University of Technology, Australia)
A single SVD sparse dictionary learning algorithm for fMRI data analysis
Muhammad Khalid (Australian National University & NICTA, Australia); Abd-krim Seghouane (The University of Melbourne, Australia)
A Non-parametric Model for Ballistocardiography
Yu Yao (ETH Zurich, Switzerland); Johannes Schiefer (RWTH Aachen University, Germany); Stefan van Waasen (Forschungszentrum Jülich GmbH, Germany); Michael Schiek (Forschungszentrum Jülich, Germany)
Estimation of High-dimensional Brain Connectivity from fMRI Data using Factor Modeling
Chee-Ming Ting (Universiti Teknologi Malaysia, Malaysia); Abd-krim Seghouane (The University of Melbourne, Australia); Sh-Hussain Salleh and Alias Mohd Noor (Universiti Teknologi Malaysia, Malaysia)
A model-free approach to increasing the effect size of fNIRS data
Adnan Shah (The Australian National University, Australia); Abd-krim Seghouane (The University of Melbourne, Australia)

MM05: Detection and estimation theory Igo to top

Chair: Linda M. Davis
Room: Interactive Session
Affine Estimation via Region Expansion
Erez Farhan (Ben-Gurion University, Israel); Rami Hagege (Ben Gurion University, Israel)
On the Perturbation of Localization Networks using Received Signal Strength
Lauren Huie (Air Force Research Lab, USA); Mark Fowler (Binghamton University, USA)
On the Relation between the Gaussian Information Bottleneck and MSE-Optimal Rate-Distortion Quantization
Michael Meidlinger, Andreas Winkelbauer and Gerald Matz (Vienna University of Technology, Austria)
Subspace detection in a kernel space: The missing data case
Tong Wu (Rutgers University, USA); Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
On the CRB for Frequency Estimation of Superimposed Multidimensional Sinusoids
Nick A Letzepis (Defence Science and Technology Group, Australia)
Minimum Mean Square Error Equalization on the 2-Sphere
Parastoo Sadeghi and Rodney Andrew Kennedy (The Australian National University, Australia); Zubair Khalid (Australian National University, Australia)
Computing persistent homology under random projection
Karthikeyan Natesan Ramamurthy and Kush Varshney (IBM Thomas J. Watson Research Center, USA); Jayaraman J Thiagarajan (Lawrence Livermore National Laboratory, USA)

Monday, June 30, 12:15 - 13:30

Lunchgo to top

Monday, June 30, 13:30 - 14:30

S2: Plenary Lecture 2: Particle Methods for Inference in Non-Linear Non-Gaussian State-Space Models (Arnaud Doucet)go to top

Arnaud Doucet, University of Oxford
Room: Grand Hall

State-space models are a very popular class of time series models which have found thousands of applications in electrical engineering, robotics, tracking, vision, econometrics etc. Except for linear and Gaussian models where the Kalman filter can be used, state and parameter inference in non-linear non-Gaussian models is analytically intractable. Particle methods are a class of flexible and easily parallelizable simulation-based algorithms which provide consistent approximations to these inference problems. The aim of this talk is to present the most recent developments in this active research area.

Monday, June 30, 14:30 - 15:00

Afternoon Teago to top

Monday, June 30, 15:00 - 17:00

MA01: Recent advances in Monte Carlo methods in statistical signal and image processinggo to top

Chair: Jean Francois Giovannelli (Special Session)
Room: Interactive Session
Robust spectral unmixing for anomaly detection
Gregory Newstadt (Google Inc, USA); Alfred Hero III (University of Michigan, USA); Jeff Simmons (AFRL, Wright-Patterson Air Force Base, USA)
Sampling from a multivariate Gaussian distribution truncated on a simplex: a review
Yoann Altmann (Heriot-Watt University); Nicolas Dobigeon (University of Toulouse, France); Steve McLaughlin (Heriot Watt University, United Kingdom (Great Britain))
Improving SMC Sampler Estimate by Recycling All Past Simulated Particles
Thi Le Thu Nguyen (Institut TELECOM/TELECOM Lille1/LAGIS UMR CNRS 8219, France); François Septier (Telecom Lille, Univ Lille, CNRS - CRIStAL, France); Gareth Peters (University College London London, United Kingdom (Great Britain)); Yves Delignon (Institut TELECOM/TELECOM Lille1 & Lagis UMR CNRS 8146, France)
Maximum marginal likelihood estimation of the granularity coefficient of a Potts-Markov Random field within an MCMC algorithm
Marcelo Pereyra, Nick Whiteley and Christophe Andrieu (University of Bristol, United Kingdom (Great Britain)); Jean-Yves Tourneret (University of Toulouse & ENSEEIHT, France)
Bayesian noise model selection and system identification based on approximation of the evidence
Jean-François Giovannelli (IMS, UMR CNRS 52 18, Université Bordeaux 1, France); Audrey Giremus (Université de Bordeaux, France)
Gaussian particle filtering in high-dimensional systems
Monica F. Bugallo and Petar M. Djurić (Stony Brook University, USA)

MA02: Learning theory and pattern recognition Igo to top

Chair: Raviv Raich
Room: Interactive Session
A greedy, adaptive approach to learning geometry of nonlinear manifolds
Talal Ahmed (Rutgers University, USA); Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
Efficient instance annotation in multi-instance learning
Anh Pham, Raviv Raich and Xiaoli Fern (Oregon State University, USA)
Maximum Likelihood Orthogonal Dictionary Learning
Muhammad Hanif (The Australian National University, Australia); Abd-krim Seghouane (The University of Melbourne, Australia)
Nonlocal Foveated Principal Components
Alessandro Foi (Tampere University of Technology, Finland); Giacomo Boracchi (Politecnico di Milano, Italy)

MA03: Adaptive systems and signal processing IIgo to top

Chair: Sven Nordholm
Room: Interactive Session
Adaptive Distributed Waveform Selection for Target Tracking by A Multistatic Radar System
Ngoc Hung Nguyen (University of South Australia, Australia); Reza Arablouei (CSIRO, Australia); Kutluyıl Doğançay (University of South Australia, Australia)
Clutter Mapping for Histogram PMHT
Samuel Davey (DSTO, Australia); Han X Gaetjens (Defence Science and Technology Group, Australia); Sanjeev Arulampalam (Defence Science and Technology Organisation, Australia); Fiona Fletcher (DSTO, Australia, Australia); Cheng-Chew Lim (University of Adelaide, Australia)
Time-frequency clustering with weighted and contextual information for convolutive blind source separation
Ingrid Jafari (FB Rice, Australia); Matt Atcheson (The University of Western Australia, Australia); Roberto Togneri (University of Western Australia, Australia); Nordholm Sven (Curtin University of Technology, Australia)
On the spurious solutions of the FastICA algorithm
Tianwen Wei (Zhongnan University of Economics and Law, P.R. China)
Adaptive Constant Modulus Algorithm Based on Complex Givens Rotations
Boudjellal Abdelouahab (Polytech'Orléans, France); Karim Abed-Meraim (Polytech'Orléans & University of Sharjah, UAE, France); Adel Belouchrani (Ecole Nationale Polythechnique, Algiers, Algeria); Philippe Ravier (Université d'Orléans, France)
A two-step optimal waveform design for detection in signal-dependent interference
Tiezhu Yuan (National University of Defense Technology, P.R. China); Zhaocheng Yang (Shenzhen University, P.R. China); Yu-Liang Qin (National University of Defense Technology, P.R. China)

MA04: Biomedical signal processing IIgo to top

Chair: Petar Djuric
Room: Interactive Session
Robust Capon Beamformer with Frequency Smoothing applied to Medical Ultrasound Imaging
Xian Long (The University of Sydney, Australia); S. M. Akramus Salehin and Thushara D. Abhayapala (Australian National University, Australia)
A Novel Feature Extraction Technique for Human Activity Recognition
Víctor Elvira (IMT Lille Douai, France); Alfredo Nazábal and Antonio Artés-Rodríguez (Universidad Carlos III de Madrid, Spain)
Symbolic Representation of Human Electromyograms for Automated Detection of Phasic Activity During Sleep
Jacqueline Fairley (Emory University & Georgia Institute of Technology, USA); Petros Karvelis (University of Ioannina, Greece); George Georgoulas and Chrysostomos Stylios (TEI of Epirus, Greece); David Rye and Donald Bliwise (Emory University, USA)
Estimating Dynamic Cortical Connectivity from Motor Imagery EEG using Kalman Smoother & EM Algorithm
S. Balqis Samdin, Chee-Ming Ting, Sh-Hussain Salleh, Mahyar Hamedi and Alias Mohd Noor (Universiti Teknologi Malaysia, Malaysia)
A Log-Ratio Pair Approach to Endoscopic Image Matching
Rohana Abdul Karim (University Malaysia Pahang, Malaysia)
Sparsity-Based Algorithms for Blind Separation of Convolutive Mixtures with Application to EMG Signals
Boudjellal Abdelouahab (Polytech'Orléans, France); Karim Abed-Meraim (Polytech'Orléans & University of Sharjah, UAE, France); Adel Belouchrani (Ecole Nationale Polythechnique, Algiers, Algeria); Philippe Ravier (Université d'Orléans, France); Abdeldjalil Aïssa-El-Bey (TELECOM Bretagne, France)

MA05: Detection and estimation theory IIgo to top

Chair: Langford White
Room: Interactive Session
Aircraft bearing estimation using underwater acoustic sensors
Kam W Lo and Brian G Ferguson (Defence Science and Technology Organisation, Australia)
Density Parameter Estimation for Additive Cauchy-Gaussian Mixture
Yuan Chen (City University of Hong Kong, Hong Kong); Ercan Engin Kuruoglu (CNR, Italy); Hing Cheung So and Long-ting Huang (City University of Hong Kong, Hong Kong); Wen-Qin Wang (University of Electronic Science and Technology of China, P.R. China)
On Fitting Exponentially Damped Sinusoids
Barry Quinn (Macquarie University, Australia)
New Normalised Bayesian Smoothers for Signals Modelled by Non-Causal Compositions of Reciprocal Chains
Langford White (The University of Adelaide, Australia); Francesco Carravetta (Consiglio Nazionale delle Ricerche, Italy)
Achievable accuracy in parameter estimation of A Gaussian plume dispersion model
Branko Ristic (RMIT University, Australia); Ajith Gunatilaka and Ralph Gailis (DSTO, Australia)
Interior point solution of fractional Bethe permanent
Jason L Williams (Defence Science and Technology Group, Australia)

Tuesday, July 1

Tuesday, July 1, 08:30 - 09:30

S3: Plenary Lecture III: Coherence as an Organizing Principle in Signal Processing (Louis Scharf)go to top

Louis Scharf, Colorado State University
Room: Grand Hall

The concepts of coherence and interference are central to optics, electromagnetics, communication, and control. Perhaps they are central to statistical signal processing, as well. In this plenary talk we shall examine this suggestion by exploring the extent to which Generalized Coherence may be used as an organizing principle in detection, estimation, and time series analysis. In so doing, we shall establish the geometries and invariances of generalized coherence, and then apply it to the analysis of several new and old problems in statistical signal processing. Of particular note is a logical derivation of what may be called broadband multi-channel coherence, a statistic whose finite sample distribution is the distribution of a product of independent beta random variables. In the main, this talk will report results and insights gained in collaboration with Doug Cochran, David Ramirez, Ignacio Santamaria, Javier Via, Peter Schreier, Nick Klausner, and Mahmood Azimi-Sadjadi.

Tuesday, July 1, 09:30 - 10:00

Morning Teago to top

Tuesday, July 1, 10:00 - 12:00

TM01: Stochastic Geometry in Signal Processinggo to top

Chair: Reza Hoseinnezhad (Special Session)
Room: Interactive Session
Faa di Bruno's formula and Volterra series
Daniel Clark (Heriot Watt, United Kingdom (Great Britain)); Jeremie Houssineau (National University of Singapore, Singapore)
Multi-Bernoulli Filter Based Hierarchical Sensor Selection for Multi-target Tracking
Nguyen-Vu Truong (Vietnam Academy of Science and Technology & Institute of Mechanics and Applied Informatics, Vietnam)
The best fitting multi-Bernoulli filter
Jason L Williams (Defence Science and Technology Group, Australia)
Information Theoretic Approach to Robust Multi-Bernoulli Sensor Control
Bayesian estimation of multi-object systems with independently identically distributed correlations
Jeremie Houssineau (National University of Singapore, Singapore); Daniel Clark (Heriot Watt, United Kingdom (Great Britain))
On the periodogram estimators of periods from interleaved sparse, noisy timing data
Barry Quinn (Macquarie University, Australia); Vaughan Clarkson (The University of Queensland, Australia); Robby G. McKilliam (University of South Australia, Australia)
A stochastic geometric approach to sensor array processing
Ba-Ngu Vo and Ba-Tuong Vo (Curtin University, Australia)
The Cauchy-Schwarz divergence for Poisson point processes
Hung G Hoang, Ba-Ngu Vo and Ba-Tuong Vo (Curtin University, Australia); Ronald P. S. Mahler (Independent Consultant, USA)

TM02: Learning theory and pattern recognition IIgo to top

Chair: Marco Duarte
Room: Interactive Session
The Sample Complexity of Dictionary Learning
Matthias Seibert and Martin Kleinsteuber (Technische Universität München, Germany); Rémi Gribonval (INRIA, France); Rodolphe Jenatton (INRIA, CMAP, France); Francis Bach (INRIA, France)
Activity Recognition Using Binary Tree SVM
Umakanthan Sabanadesan (Queensland University Of Technology, Australia); Simon Denman, Clinton Fookes and Sridha Sridharan (Queensland University of Technology, Australia)
Masking Schemes for Image Manifolds
Hamid Dadkhahi and Marco F Duarte (University of Massachusetts, USA)
Asymptotic Inference for Hidden Process Regression Models
Hien Nguyen (University of Queensland & School of Mathematics and Physics, Australia); Geoffrey McLachlan (University of Queensland, Australia)

TM03: Monte Carlo methods Igo to top

Chair: Ba-Ngu Vo
Room: Interactive Session
Soft systematic resampling for accurate posterior approximation and increased information retention in particle filtering
Praveen Choppala, Marcus Frean and Paul D Teal (Victoria University of Wellington, New Zealand)
Sphere Decoding Inspired Approximation Method to Compute the Entropy of Large Gaussian Mixture Distributions
Su Min Kim (Korea Polytechnic University, Korea); Tan Tai Do (KTH, Royal Institute of Technology & School of Electrical Engineering, Sweden); Tobias J. Oechtering (KTH Royal Institute of Technology & School of Electrical Engineering, EE, Sweden); Gunnar Peters (Huawei, Sweden)
Robust Auxiliary Particle Filters using Multiple Importance Sampling
Joel Kronander (Linköping University, Sweden); Thomas B. Schön (Uppsala University, Sweden)
Rao-Blackwellized Particle Filter for Markov Modulated Nonlinear Dynamic Systems
Saikat Saha (GE Research Bangalore, India); Gustaf Hendeby (Linköping University, Sweden)
Sequential Monte Carlo Samplers for Marginal Likelihood Computation in Multiplicative Exponential Noise Models
Onur Dikmen (University of Helsinki, Finland); Ali Taylan Cemgil (Bogazici University, Turkey)

TM04: Compressed Sensing Igo to top

Chair: Robert Nowak
Room: Interactive Session
On the Sample Complexity of Subspace Clustering with Missing Data
Daniel L Pimentel-Alarcon (University of Wisconsin-Madison, USA); Laura Balzano (University of Michigan, USA); Robert Nowak (University of Wisconsin - Madison, USA)
A Sparsity based approach for Acoustic Room Impulse Response Shortening
Lakshmi Krishnan (Victoria University of Wellington); Paul D Teal (Victoria University of Wellington, New Zealand); Terence Betlehem (Samsung Electronics Digital Media and Communications Centre, Korea)
Continuous Compressed Sensing With a Single or Multiple Measurement Vectors
Zai Yang (Nanjing University of Science and Technology, Singapore); Lihua Xie (Nanyang Technological University, Singapore)
Quasi-Equiangular Frames (QEFs): A New Flexible Configuration of Frames
Hailong Shi (Tsinghua University & Department of Electronic Engineering, P.R. China); Hao Zhang (TsinghuaUniversity, P.R. China); Xiqin Wang (Tsinghua University, P.R. China)

TM05: Detection and estimation theory IIIgo to top

Chair: Branko Ristic
Room: Interactive Session
Autonomous information driven search for a diffusive source in an unknown structured environment
Branko Ristic (RMIT University, Australia); Alex Skvortsov (Defence Science and Technology Organisation, Australia); Andrew Walker (DSTO, Australia)
MUSIC-based DOA Estimation by Oblique Projection Along The Signal Subspace
Akira Tanaka and Hideyuki Imai (Hokkaido University, Japan)
Multiplicative regression via constrained least squares
Dennis Wei (IBM T. J. Watson Research Center, USA); Karthikeyan Natesan Ramamurthy (IBM Thomas J. Watson Research Center, USA); Dmitriy Katz and Aleksandra Mojsilovic (IBM T.J. Watson Research Center, USA)
$\ell_1$-norm based nonparametric and semiparametric approaches for Robust Spectral Analysis
Yuan Chen, Hing Cheung So and Long-ting Huang (City University of Hong Kong, Hong Kong); Wen-Qin Wang (University of Electronic Science and Technology of China, P.R. China)
Multiple Shift Maximum Element Sequential Matrix Diagonalisation for Parahermitian Matrices
Jamie Corr, Keith Thompson and Stephan Weiss (University of Strathclyde, United Kingdom (Great Britain)); John G McWhirter (Cardiff University, United Kingdom (Great Britain)); Soydan Redif (European University of Lefke, Cyprus); Ian Proudler (Loughborough University, United Kingdom (Great Britain))

Tuesday, July 1, 12:00 - 13:30

Lunchgo to top

Tuesday, July 1, 13:30 - 14:30

S4: Plenary Lecture IV: Sparse stochastic processes, matched wavelet expansions and ICA (Michael Unser)go to top

Michael Unser, École Polytechnique Fédérale De Lausanne (EPFL)
Room: Grand Hall

We introduce an extended family of continuous-domain sparse processes that are specified by a generic (non-Gaussian) innovation model or, equivalently, as solutions of linear stochastic differential equations driven by white Lévy noise. We present the functional tools for their characterization. We show that their probability distributions are infinitely divisible, which induces two distinct types of behavior—Gaussian vs. sparse—at the exclusion of any other. This is the key to proving that the non-Gaussian members of the family admit a sparse representation in a matched wavelet basis.

We use the characteristic form of these processes to deduce their transform-domain statistics and to precisely assess residual dependencies. These ideas are illustrated with examples of sparse processes for which operator-like wavelets outperform the classical KLT (or DCT) and result in an independent component analysis. Finally, for the case of self-similar processes, we show that the wavelet-domain probability laws are ruled by a diffusion-like equation that describes the evolution across scale.

Tuesday, July 1, 14:30 - 15:00

Afternoon Teago to top

Tuesday, July 1, 15:00 - 17:00

TA01: Advances in robust statistical signal processing Igo to top

Chair: Abdelhak Zoubir (Special Session)
Room: Interactive Session
Performance Analysis of Recursive Least Normalized Correlation Norms Algorithm
Shin'ichi Koike (Consultant, Japan)
Delay-Doppler Average Ambiguity Function for Array Radar with Stochastic Signals
Guofeng Zha (Natinal University of Defense and Technology, P.R. China)
Shrinkage covariance matrix estimator applied to STAP detection
Frederic Pascal (CentraleSupélec, France); Yacine Chitour (Universite Paris XIII, France)
Regularized Successive Interference Cancellation (SIC) Under Mismatched Modeling
Jun Tong (University of Wollongong, Australia); Li Li (University of Paderborn, Germany); Qinghua Guo (University of Wollongong & University of Western Australia, Australia); Peter J. Schreier (Universitaet Paderborn, Germany); Jiangtao Xi (University of Wollongong, Australia)
Robust Bootstrap Based Observation Classification for Kalman Filtering in Harsh LOS/NLOS Environments
Stefan Vlaski (University of California, Los Angeles, USA); Abdelhak M Zoubir (Darmstadt University of Technology, Germany)
Estimation under Additive Cauchy-Gaussian Noise Using Markov Chain Monte Carlo
Yuan Chen (City University of Hong Kong, Hong Kong); Ercan Engin Kuruoglu (CNR, Italy); Hing Cheung So (City University of Hong Kong, Hong Kong)

TA02: Array processing, radar and sonargo to top

Chair: Douglas Cochran
Room: Interactive Session
Terahertz Radar Imaging Based on Block Sparse Bayesian Learning Framework
Ruijun Wang, Bin Deng, Yu-Liang Qin, Yongqiang Cheng and Wuge Su (National University of Defense Technology, P.R. China)
Constant Turn Model for Converted Doppler Measurement Kalman Filter
Gongjian Zhou (Harbin Institute of Technology, P.R. China)
DOA Estimation in the Presence of Array Imperfections: A Sparse Regularization Parameter Selection Problem
Christian Weiss and Abdelhak M Zoubir (Darmstadt University of Technology, Germany)
Invariance of the Distributions of Normalized Gram Matrices
Stephen D Howard (Defence Science & Technology Organisation, Australia); Songsri Sirianunpiboon (Defence Science and Technology Group, Australia); Douglas Cochran (Arizona State University, USA)
Using Direction of Arrival Arrays with Unknown Orientation
Oren Jean and Anthony J. Weiss (Tel Aviv University, Israel)

TA03: Monte Carlo methods IIgo to top

Chair: Jason Williams
Room: Interactive Session
MCMC methods for univariate exponential family models with intractable normalization constants
David Rohde and Jonthan Corcoran (University of Queendland, Australia)
An improved Bayesian inversion method for the estimation of multimodal particle size distributions using multiangle dynamic light scattering measurements
Abdelbassit Boualem, Meryem Jabloun and Philippe Ravier (Université d'Orléans, France); Marie Naiim and Alain Jalocha (CILAS, France)
Orthogonal MCMC algorithms
Luca Martino (University of Helsinki, Finland); Víctor Elvira (IMT Lille Douai, France); David Luengo (Universidad Politecnica de Madrid (UPM), Spain); Antonio Artés-Rodríguez (Universidad Carlos III de Madrid, Spain); Jukka Corander (University of Helsinki, Finland)
Backward sequential Monte Carlo for marginal smoothing
Joel Kronander (Linköping University, Sweden); Thomas B. Schön (Uppsala University, Sweden); Johan Dahlin (Linköping University, Sweden)
Gossip-Based Distributed Data Fusion of Empirical Probability Measures
Adrian Bishop (NICTA, Canberra Research Laboratory & Australian National University (ANU), Australia)

TA04: Compressed sensing IIgo to top

Chair: Yuejie Chi
Room: Interactive Session
New Coherence and RIP Analysis for Weak Orthogonal Matching Pursuit
Mingrui Yang (Case Western Reserve University, USA); Frank de Hoog (CSIRO, Australia)
Sparse Recovery on Sphere via Probabilistic Compressed Sensing
Yibeltal Fantahun Alem and Daniel H. Chae (The Australian National University, Australia); S. M. Akramus Salehin (Australian National University, Australia)
Compressive Parameter Estimation With Multiple Measurement Vectors via Structured Low-Rank Covariance Estimation
Yuanxin Li and Yuejie Chi (The Ohio State University, USA)
Complexity-Adaptive Universal Signal Estimation for Compressed Sensing
Junan Zhu (NCSU, USA); Dror Baron (North Carolina State University, USA); Marco F Duarte (University of Massachusetts, USA)
Performance Analysis For Matrix Completion via Iterative Hard-Thresholded SVD
Evgenia Chunikhina and Raviv Raich (Oregon State University, USA); Thinh Nguyen (Oregon State, USA)
Sparse posterior probability support vector machines
Dongli Wang and Yan Zhou (Xiangtan University, P.R. China)

TA05: Communication systems and networks Igo to top

Chair: Yue Rong
Room: Interactive Session
Blind Estimation of MIMO Relay Channels
Choo Chiong (Curtin University, Malaysia); Yue Rong (Curtin University, Australia); Yong Xiang (Deakin University, Australia)
Cooperative Spectrum Sensing Using Double Thresholds Energy Detection and Adaptive Grid Search Algorithm in Cognitive Radio Networks
Tangsen Huang (South China University of Technology, P.R. China)
Outage Optimal Relay Selection Strategy Using Destination- Based Jamming for Secure Communication in Amplify-and-Forward Relay Networks
Sarbani Ghose (Indian Statistical Institute Kolkata, India); Ranjan Bose (Indian Institute of Technology, India)
Semi-infinite Quadratic Programming Approach to Design FIR Filter for PAPR Reduction in OFDM System
Regina Reine (Curtin University Sarawak Campus, Malaysia); Zhuquan Zang (Curtin University. Malaysia, Malaysia)
Statistical Analysis of Multiple Access Interference in Rayleigh Fading Environment for MIMO CDMA Systems
Khalid Mahmood (King Fahd University of Minerals and Petroleum Saudi Arabia, Saudi Arabia); Syed M Asad (University of Hafr Al Batin, Saudi Arabia); Muhammad Moinuddin (King Abdul Aziz University, Saudi Arabia); Azzedine Zerguine (KFUPM, Saudi Arabia); Shashi Paul (Emerging Technologies Research Centre, United Kingdom (Great Britain))

Tuesday, July 1, 19:00 - 21:00

Conference Dinnergo to top

Room: Grand Hall

Wednesday, July 2

Wednesday, July 2, 08:30 - 09:30

S5: Plenary Lecture V: The Square Kilometre Array: new paradigms required for signal processing in astronomy (Steven Tingay)go to top

Steven Tingay, Curtin University
Room: Grand Hall

I will describe the Square Kilometre Array (SKA), a multi-billion dollar radio telescope being designed and built by a large international consortium. The SKA will be built in Western Australia and Southern Africa and will produce vast amounts of data, driving new approaches to signal processing in order to achieve the performance specifications required by the scientific goals. I'll briefly outline the science and engineering of the SKA, discuss prototype telescopes currently operating, and focus on the Big Data problem that needs to be addressed from algorithmic and computational points of view.

Wednesday, July 2, 09:30 - 10:30

S6: Plenary Lecture VI: Enabling Functional Neuro-imaging with Statistical Signal Processing (Victor Solo)go to top

Victor Solo, University of New South Wales
Room: Grand Hall

Functional Magnetic Resonance Imaging (fMRI) has caused a revolution in cognitive neuroscience since its advent in the early 1990s because of its ability to show the brain 'in action'. Its dominant position is due to several features: it is non-invasive and so when properly used is nearly harmless; it provides spatial and temporal resolution relevant to brain dynamics; and it is very flexible allowing the kind of image sequences produced to be tailored to the scientific questions of interest. But fMRI is useless without some fundamentally enabling methodologies.

Chief amongst these is statistical signal processing and we give a brief survey of fMRI from this point of view. We give some physics background; we identify the basic scientific and statistical signal processing issues; and based on our own work we show advanced techniques in action; sparsity for activation map production; problems with Granger causality; brain network analysis using multivariate mutual information. We also discuss briefly multi-modal brain imaging involving EEG, MEG, fMRI.

Wednesday, July 2, 10:30 - 11:00

Morning Teago to top

Wednesday, July 2, 11:00 - 13:00

WM01: Advances in robust statistical signal processing IIgo to top

Chair: Abdelhak Zoubir (Special Session)
Room: Interactive Session
Robust Gaussian Sum Filtering with Unknown Noise Statistics: application to target tracking
Jordi Vilà-Valls (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Spain); Qi Wei (Duke University, USA); Pau Closas (Northeastern University, USA); Carles Fernández-Prades (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain)
Robust iteratively reweighted LASSO for sparse tensor factorizations
Hyon-Jung Kim, Esa Ollila and Visa Koivunen (Aalto University, Finland); H. Vincent Poor (Princeton University, USA)
Improving Model-Based Convolutive Blind Source Separation Techniques via Bootstrap
Swati Chandna and Wenwu Wang (University of Surrey, United Kingdom (Great Britain))
Robust model order selection for ARMA models based on the bounded innovation propagation τ-estimator
Michael Muma (Darmstadt University of Technology, Germany)
Robust Hypothesis Testing With Composite Distances
Gökhan Gül and Abdelhak M Zoubir (Darmstadt University of Technology, Germany)

WM02: Radar Processinggo to top

Chair: Kutluyıl Doğançay
Room: Interactive Session
Rare-Event Simulation for Radar Threshold Estimation in Heavy-Tailed Sea Clutter
Josef Zuk (DSTO, Australia); Luke Rosenberg (DSTO & University of Adelaide, Australia)
Statistical Spatial Resolution Limit for Ultrawideband MIMO Noise Radar
Xiaoli Zhou (National Universityof Defense Technology, P.R. China); Hong-Qiang Wang, Yongqiang Cheng and Yu-Liang Qin (National University of Defense Technology, P.R. China)
Joint Transmitter Waveform and Receiver Path Optimization for Target Tracking by Multistatic Radar System
Ngoc Hung Nguyen, Kutluyıl Doğançay and Linda M. Davis (University of South Australia, Australia)
Sparse Bayesian SAR Imaging of Moving Target Via the ExCoV Method
Wuge Su, Hong-Qiang Wang, Bin Deng and Ruijun Wang (National University of Defense Technology, P.R. China)
A search-and-revisit scanning policy to improve the detection rate in agile-beam radars
Emanuele Grossi (University of Cassino and Southern Lazio & Consorzio Nazionale Inter-universitario per le Telecomunicazioni (CNIT), Italy); Marco Lops (University of Cassino & CNIT - Consorzio Universitario Nazionale per le Telecomunicazioni, Italy); Luca Venturino (Universita' degli Studi di Cassino e del Lazio Merdionale & Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Italy)
Analysis of two-dimensional spectrum for geosynchronous SAR
Zhuoqun Wang (Harbin Institute of Technology & School of Electronics and Information Engineering, P.R. China); YIcheng Jiang, Yajun Li and Gongjian Zhou (Harbin Institute of Technology, P.R. China)

WM03: Adaptive systems and signal processing IIIgo to top

Chair: Fabrice Labeau
Room: Interactive Session
Asymptotic analysis of the generalized symmetric FastICA algorithm
Tianwen Wei (Zhongnan University of Economics and Law, P.R. China)
Optimal Variable Step-Size Diffusion LMS Algorithms
Saeed Ghazanfari-Rad and Fabrice Labeau (McGill University, Canada)
Upper-bounding bias errors in satellite navigation
Takashi Iwamoto (Mitsubishi Electric Corporation, Japan)
The Generalized Haar-Walsh Transform
Jeff Irion and Naoki Saito (University of California, Davis, USA)

WM04: Learning theory and pattern recognition IIIgo to top

Chair: Reza Adhami
Room: Interactive Session
Learning a hierarchical dictionary for single-channel speech separation
Guangzhao Bao, Yangfei Xu and Xu Xu (University of Science and Technology of China, P.R. China); Zhongfu Ye (University of Science & Technology of China, P.R. China)
Gaussian Mixture Models With Class-dependent Features for Speech Emotion Recognition
Rafael Iriya and Miguel Arjona Ramírez (University of São Paulo, Brazil)

WM05: Communication systems and networks IIgo to top

Chair: Paul Teal
Room: Interactive Session
Recognition of Polyphase Coded Signals Using Time-frequency Rate Distribution
Lin Li (Xidian University, P.R. China); Li Jiang (Xi'an University of Architecture and Technology, P.R. China)
Simultaneous Channel Estimation and Joint Time-Frequency Domain Crosstalk Cancellation in Multichannel Personal Audio Systems
Harsh Tataria (Queen's University Belfast, United Kingdom (Great Britain)); Paul D Teal (Victoria University of Wellington, New Zealand); Mark Poletti (Callaghan Innovation, New Zealand); Terence Betlehem (Samsung Electronics Digital Media and Communications Centre, Korea)
Energy-efficient coordinated beamforming in downlink OFDMA cellular networks
Luca Venturino (Universita' degli Studi di Cassino e del Lazio Merdionale & Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Italy); Stefano Buzzi (University of Cassino and Lazio Meridionale/CNIT, Italy)
A Novel Pairing Scheme to Reduce Error Propagation in an Amplify and Forward Multi-way Relay Network
Shama N. Islam (Deakin University, Australia); Parastoo Sadeghi and Salman Durrani (The Australian National University, Australia)
Non-Cooperative Feedback Control Game Under a Sum Feedback-Rate Constraint in MIMO Broadcast Channels
Seonghun Yun (Korea Advanced Institute of Science and Technology, Korea); Jungho Myung (Electronics and Telecommunications Research Institute, Korea); Wonju Lee (Samsung Advanced Institute of Technology, Korea); Joonhyuk Kang (KAIST, Korea)

WM06: System identification and calibrationgo to top

Chair: Daniel Clark
Room: Interactive Session
Radiolocation and Tracking of Automatic Identification System Signals
Francesco Papi (Curtin University, Australia); Dario Tarchi (IPSC, Joint Research Centre, European Commission, Italy); Michele Vespe (European Commission - Joint Research Centre (JRC), Italy); Franco Oliveri (IPSC, Joint Research Centre, European Commission, Italy); Giuseppe Aulicino (Italian Coast Guard, Italy)
Bayesian calibration of the Schwartz-Smith Model adapted to the energy market
Saikat Saha (GE Research Bangalore, India)
On the Efficiency of an Autonomous Cyclic Motion Grading System
Sanam Moghaddamnia (Leibniz University of Hannover, Germany); Jürgen Peissig (Leibniz Universität Hannover, Germany); Gerd Schmitz (Leibniz Universitaet Hannover, Germany); Alfred Effenberg (Leibniz Universit¨at Hannover, Germany)
Cooperative sensor localisation in Distributed Fusion Networks by exploiting non-cooperative targets
Murat Uney (The University of Edinburgh, United Kingdom (Great Britain)); Bernard Mulgrew (Institute for Digital Communications, The University of Edinburgh, United Kingdom (Great Britain)); Daniel Clark (Heriot Watt, United Kingdom (Great Britain))

Wednesday, July 2, 13:00 - 14:30

Lunchgo to top