Tsachy Weissman's Current Research

 

 

  Areas of interest:

- Information Theory

- Statistical Signal Processing

 

Some recent work (final published versions may differ from manuscripts in links):

Denoising:

T.  Weissman, E. Ordentlich, G. Seroussi, S. Verdu and M. Weinberger, ``Universal  Discrete Denoising: Known Channel’’, IEEE Trans. Inform. Theory, vol. 51, n0. 1, pp 5-28, January 2005. Click here for a DUDE demonstration.

A. Dembo and T. Weissman, ``Universal Denoising for the Finite-Input-General-Output Channel'', to appear in IEEE Trans. Inform. Theory.   

G. Gemelos, S. Sigurjonsson and T. Weissman, ``Universal Minimax Discrete Denoising under Channel Uncertainty'', submitted to IEEE Trans. Inform. Theory. See also here for a conference version containing additional related results.  

G. Gemelos, S. Sigurjonsson and T. Weissman, ``Algorithms for Discrete Denoising Under Channel Uncertainty'', Submitted to IEEE Trans. Signal Processing. See also here for applications to binary image denoising. 

R. Zhang and T. Weissman, ``Discrete Denoising for Channels with Memory'', submitted to Communications in Informations and Systems, special issue in celebration of Professor Thomas Kailath's 70th birthday. See also here for a conference version focusing on applications to the burst noise channel.

E. Ordentlich, M. J. Weinberger and T. Weissman, Efficient Pruning of Bi-Directional Context Trees with Applications to Universal Denoising and Compression, San Antonio Information Theory Workshop, October 2004.
 

 Shannon Theory:

T.  Weissman and E. Ordentlich, ``The empirical distribution of rate-constrained codes", to appear in IEEE Trans. Inform. Theory.

E. Ordentlich and T. Weissman, New Bounds on the Entropy Rate of Hidden Markov Processes, San Antonio Information Theory Workshop, October 2004.

 

Filtering:

E. Ordentlich and T. Weissman, ``On the optimality of symbol-by-symbol filtering and denoising'', to appear in IEEE Trans. Inform. Theory.   

E. Ordentlich, T. Weissman, M. Weinberger, Anelia Somekh-Baruch and Neri Merhav, ``Discrete Universal Filtering Through Incremental Parsing'', DCC2004.

 

Joint Source-Channel Coding:

S. Matloub and T. Weissman, "Universal zero-delay joint source-channel coding", submitted to IEEE Trans. Inform. Theory. (see also conference version).  

 

Source Coding:  

T. Weissman and N. Merhav, ``On Causal Source Codes with Side Information,'' submitted to IEEE Trans. Inform. Theory.

T.  Weissman ``Not all universal source codes are pointwise universal", submitted to IEEE Trans. Inform. Theory.

G. Gemelos and T. Weissman, "On the entropy rate of pattern processes", to appear in DCC2005.

 

Rate Distortion Coding of Noisy Sources:

T. Weissman, ``Universally Attainable Error-Exponents for Rate-Distortion Coding of Noisy Sources,” IEEE Trans. Inform. Theory, vol. 50, no. 6, pp. 1229-1246, June 2004.

 

Prediction:

T. Weissman and N. Merhav, ``Universal prediction of random binary sequences in a noisy environment,'' The Annals of Applied Probability, Vol. 14, No. 1, February 2004. 

N. Merhav and T. Weissman, ``Scanning and prediction in multi-dimensional data arrays,'' IEEE Trans. Inform. Theory, vol. IT-49, no. 1, pp. 65-82, January 2003.  

T. Weissman and N. Merhav, ``On competitive predictability and its relation to rate-distortion theory''  IEEE Trans. Inform. Theory, vol. IT-49, no. 12, pp. 3185-3194, December 2003.

 

 

Recent Talks:

"On optimal filtering and entropy rate of a hidden Markov process ", Berkeley EECS dept.

"Discrete Universal Filtering (Through Incremental Parsing)", Princeton EE dept. and Wharton school Statistics dept.

"Universal Minimax Discrete Denoising under Channel Uncertainty", UCSD EECS dept.

"New Bounds on the Entropy Rate of Hidden Markov Processes", ISL Colloquium, Stanford University.