Design of Optimal Quantizers for Distributed Source Coding
DCC '03 Proceedings of the Conference on Data Compression
Design of Trellis Codes for Source Coding with Side Information at the Decoder
DCC '01 Proceedings of the Data Compression Conference
On Multiterminal Source Code Design
DCC '05 Proceedings of the Data Compression Conference
On Efficient Quantizer Design for Robust Distributed Source Coding
DCC '06 Proceedings of the Data Compression Conference
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ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04
The CEO problem [multiterminal source coding]
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IEEE Transactions on Information Theory
Multiple description quantization by deterministic annealing
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Rate Region of the Quadratic Gaussian Two-Encoder Source-Coding Problem
IEEE Transactions on Information Theory
On Multiterminal Source Code Design
IEEE Transactions on Information Theory
Robust Distributed Source Coding
IEEE Transactions on Information Theory
Error-resilient and complexity-constrained distributed coding for large scale sensor networks
Proceedings of the 11th international conference on Information Processing in Sensor Networks
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This paper considers the design of efficient quantizers for a robust distributed source coding system. The information is encoded at independent terminals and transmitted across separate channels, any of which may fail. The scenario subsumes a wide range of source and source-channel coding/quantization problems, including multiple descriptions and distributed source coding. Greedy descent methods depend heavily on initialization, and the presence of abundant (high density of) "poor" local optima on the cost surface strongly motivates the use of a global design algorithm. We propose a deterministic annealing approach for the design of all components of a generic robust distributed source coding system. Our approach avoids many poor local optima, is independent of initialization, and does not make any simplifying assumption on the underlying source distribution. Simulation results demonstrate a wide spread in the performance of greedy Lloyd-based algorithms, and considerable gains are achieved by using the proposed deterministic annealing approach.