July to December 1998

**Organisers**: W J Fitzgerald (*Cambridge*), R L Smith (*University of North Carolina*), A Walden (*Imperial College, London*) and P C Young (*Lancaster University*)

*Organisers: WJ Fitzgerald (Cambridge), RL Smith (North Carolina),
AT Walden (Imperial), PC Young (Lancaster) *

The main focus and thrust of this workshop will be that Bayesian methods provide a unifying methodology whereby different kinds of mathematical models may be examined within a common statistical framework. The workshop will bring together the statistical and computational expertise of leading statisticians and the modelling expertise of mathematicians and subject matter specialists, with the broad objective of developing new signal processing tools which make efficient use of modern computational resourc es while combining the most up-to-date research of both groups of specialists.

The workshop will take place at the start of a six month programme on Nonlinear and Nonstationary Signal Processing to be held at the Isaac Newton Institute in Cambridge (July - Dec 1998), where it is hoped that many of the problems identified during the workshop will be studied in detail by the participants.

**7pm - ...(please note change from 6pm) ** Reception at
Christ's College

**09.00 - 10.00 Registration **

**10.00-11.00** **W J Fitzgerald** (Cambridge)

*An Introduction to Bayesian Signal Processing I*

**11.00-11.30 Coffee **

**11.30-12.30 W J Fitzgerald** (Cambridge)

*An Introduction to Bayesian Signal Processing II*

**12.30-14.00 Lunch **

**14.00-15.00 C Robert** (Paris)

*Latent Variable Models*

**15.00-15.30 Tea **

**15.30-16.30 C Robert **(Paris)

*The Simulated Likelihood Method*

**10.00-11.00 P J W Rayner** (Cambridge)

*Non-linear Signal Modelling - a Tutorial I*

**11.00-11.30 Coffee**

**11.30-12.30 P J W Rayner** (Cambridge)

*Non-linear Signal Modelling - a Tutorial II*

**12.30-14.00 Lunch**

**14.00-15.00 J A Stark** (NISS and Cambridge)

*MCMC Methods for Multiple Changepoint Inference*

**15.00-15.30 F Gustafsson **(Sweden)

*Automotive applications on adaptive filtering and change*

**15.30-16.00 Tea **

**16.00-17.00 J Scargle** (NASA)

*Multiple Change Point Determination for Point Processes*

**10.00-11.00 C Bishop** (Microsoft Research)

*Introduction to Probabilistic Graphical Models I*

**11.00-11.30 Coffee**

**11.30-12.30 C Bishop** (Microsoft Research)

*Introduction to Probabilistic Graphical Models II*

**12.30-14.00 Lunch **

**14.00-15.00 D Spiegelhalter** (Cambridge)

*Bayesian graphical modelling of complex applications *

**15.00-15.30 Tea **

**15.30-16.30** Introduction to 'BUGS'

**16.45 -17.45 David Mackay **(Cambridge)

*Latent Variable Models and Neural Networks*

**6.00- ... **Wine reception and Buffet (Sponsored by Cambridge
Neurodynamics and Autonomy)

**Posters**

**9.00-10.00 M Niranjan** (Cambridge)

*Bayesian Techniques in Speech Signal Processing*

**10.00-11.00 David Mackay** (Cambridge)

*State of the art in error correcting codes*

**11.00-11.30 Coffee **

**11.30-12.30 S J Godsill** (Cambridge)

*Bayesian methods for non-Gaussian signal processing*

**12.30-14.00 Lunch **

**14.00-14.30 F Gustafsson** (Sweden)

*MDL as a performance measure for choosing adaptive filters.*

**14.30-16.00 M Pitt **(Imperial College)

*Filtering and Smoothing for Non-Gaussian state space models*

**16.00-16.30 Tea**

**16.30-17.30 John Skilling** (Cambridge)

*Annealing and Ensembles*

**10.00-11.00 Giulio D'agostini (Rome)
**

**11.00-11.30 Coffee **

**11.30-12.30 Giulio D'agostini** (Rome)

*A Tutorial on Measurement Uncertainty II*

**12.30-14.00 Lunch **

**14.00-15.00 Siddhartha Chib, Neil Shephard and Ola Elerian**

*Likelihood inference for discretely observed non-linear diffusions*

**15.00-16.00 V Krishnamurthy**

*Iterative Maximum A-posteriori Sequence Estimation for Nonlinear Systems*

**16.00-16.30 Tea**

**16.30-17.30 A Hyvarinen** (Finland)

*Independent Component Analysis, Blind Source Separation, and Projection
Pursuit*

19.30 Conference Dinner (Christ's College)

Sunday 26 July Punting etc.

**9.00-10.00 Mike West** (Duke)

*
Decomposition Methods In Nonstationary Signal Processing*

**10.00-11.00 A Walden** (Imperial College)

*Scale Analysis of Time Series*

**11.00-11.30 Coffee **

**11.30-12.30 R Baraniuk**

*Wavelet-domain statistical signal and image processing using hidden
markov models*

**12.30-14.00 Lunch **

**Cricket Match and Barbeque**

**10.00-11.00 R Nowak**

*Bayesian Analysis of Poisson Processes: A Wavelet-Based Approach*

**11.00-11.30 Coffee **

**11.30-12.30 B Vidakovic (Duke)**

*Nonlinear Bayesian Shrinkage in the Wavelet Domain by Mixtures of Normal-Inverse
Gamma Priors*

**12.30-14.00 Lunch **

**14.00-15.00 P Mueller (Duke)**

*Bayesian Inference with Wavelets: The Non-Equidistant Case - An MCMC
Scheme*

**15.00-16.00 D Denison** (Imperial College)

*Nonparametric Bayesian models for regression*

**16.00-16.30 Tea**

**16.30-17.00 M Hild (Cambridge)**

*A Non-Probabilistic Measure of Plausibility*

**16.00 - 18.30 Posters**

**10.00 -11.00 N Shephard** (Oxford)

*An example of signal processing in finance: stochastic volatility*

**11.00-11.30 Coffee**

**11.30-12.30 P C Young** (Lancaster)

*Recursive estimation of time and state dependent parameters using fixed
interval smoothing*

**12.30-14.00 Lunch **

**14.00-14.30 A Doucet** (Cambridge)

*MCMC Methods for Blind Bayesian Deconvolution*

**14.30-15.00 C Andrieu** (Cambridge)

*MCMC Methods for Bayesian Spectral Analysis*

**15.00-16.00 AP Quinn **(TCD)

*Bayesian perspectives on signal identification*

**16.00-16.30 Tea**

**16.30-17.30 E Moulines and O Cappe** (Paris)

*Estimation via simulation with applications to statistical inference
in incomplete data models*

**9.00 -11.00 R Smith**

*Spatial Statistics*

**11.00-11.30 Coffee **

**11.30-12.30 S Wilson **(TCD, Dublin)

*Bayesian Image Segmentation*

**12.30-14.00 Lunch **

**14.00-15.00 A Kokaram** (TCD, Dublin)

*Joint Detection and Removal of Missing Data for Degraded Image Sequences*

**15.00-16.00 A Hero**

*Robust Entropy Estimation via Pruned Minimal Spanning Trees*

**16.00-16.30 Tea **

**16.30-17.30 Roderick Murray-Smith** (Denmark)

*Multiple Model Approaches to Empirical Modelling*

**10.00 -11.00 P Djuric **(Stony Brook)

*On variable duration Hidden Markov Models*

**11.00-11.30 Coffee**

**11.30-12.30 R Elliott** (Canada)

*Kronecker's Lemma and parameter estimation *

**12.30-14.00 Lunch **

**14.00-15.00 J Scargle** (NASA)

*Exciting Events in the Universe*

**15.00-16.00 R Kohn (New South Wales)**

*Inference for dynamic mixture models *

**16.00-16.30 Tea**

**16.30-17.30 Leonard Smith** (Oxford)

*Shadowing and the dynamics of uncertainty within a given model class*

**17.30-18.00 Closing words**

1) Albert C.S. Wong

*On a Mixture Autoregressive Model*

2) Maria Eduarda R. P. A. da Silva

*Frequency Domain Estimation of Hidden Markov Autoregressive Models.*

3) Dr. Gul Ergun*
Bayesian Modelling of the Istanbul Stock Exchange. *

4) Bart Mertens

*Bayesian prediction with latent growth models for on-line monitoring
in cheese manufacture. *

6) James Heald

*Use of the Evidence method to estimate appropriate measurement and dynamical
noise levels for chaotic noise reduction*

7) V. B. Mani Mohan and W. J. Fitzgerald

*Bayesian estimation in the cyclic correlation domain*

8) Jacek Noga and W. J. Fitzgerald

*Hybrid Monte Carlo for State Space Models*

9) Simon Barker

*MCMC approaches applied to Image Segmentation.*

10) Jasvinder Kandola

*Statistical Modelling of Manufacturing Processes. *

11) Colin Campbell and S J Godsill

*Simulation for conditionally Gaussian time series using a stochastic
version of EM*

12) J A Stark, W J Fitzgerald and S B Hladky

*MCMC Modelling of Ion Channels*

13) B Kannan and W J Fitzgerald

*A Numerical Bayesian Approach for DOA and Frequency Estimation of Exponential
Signals in Gaussian and Non-Gaussian Noise. *

14) JFG de Freitas

*Sequential Monte Carlo Methods Applied to Neural Networks in Non-Linear,
Non-Stationary Environments*

15) Mike Davies

*Blind Signal Separation using Independent AR models*

16) T Clapp

*Fixed-lag Smoothing using Sequential Importance Sampling*

17) Jaco Vermaak

*MCMC Estimation of a Speech Production Model for Voiced Sounds*

18) David Leporini

*Reversible jump MCMC methods for wavelet packet decompostion of transient
signals*

19) Paul T. Troughton and Simon J. Godsill

*MCMC Methods for Restoration of Nonlinearly Distorted
Autoregressive Signals *

20) Bruno Sanso ISDS, Duke University

*
A Multisite Dynamic Model for Rainfall*

21)Paul Walmsley, Simon Godsill and Peter Rayner

*Multidimensional Optimisation of Harmonic Signals*