Learning automata: an introduction
Learning automata: an introduction
Image and Video Compression Standards: Algorithms and Architectures
Image and Video Compression Standards: Algorithms and Architectures
Utilizing Soft Information in Decoding of Variable Length Codes
DCC '99 Proceedings of the Conference on Data Compression
Iterative Source/Channel-Decoding Using Reversible Variable Length Codes
DCC '00 Proceedings of the Conference on Data Compression
Joint Source-Channel Soft Decoding of Huffman Codes with Turbo-Codes
DCC '00 Proceedings of the Conference on Data Compression
Joint Source/Channel Coding for Variable Length Codes
DCC '98 Proceedings of the Conference on Data Compression
Optimal Decoding of Entrophy Coded Memoryless Sources over Binary Symmetric Channels
DCC '98 Proceedings of the Conference on Data Compression
DCC '02 Proceedings of the Data Compression Conference
Detection of binary Markov sources over channels with additive Markov noise
IEEE Transactions on Information Theory
Tradeoff between source and channel coding
IEEE Transactions on Information Theory
A communication channel modeled on contagion
IEEE Transactions on Information Theory
The source-channel separation theorem revisited
IEEE Transactions on Information Theory
An error resilient scheme for image transmission over noisy channels with memory
IEEE Transactions on Image Processing
Bit allocation for joint source/channel coding of scalable video
IEEE Transactions on Image Processing
Adaptive quantization and fast error-resilient entropy coding for image transmission
IEEE Transactions on Circuits and Systems for Video Technology
Soft source decoding with applications
IEEE Transactions on Circuits and Systems for Video Technology
Cross-layer optimized wireless multicast for layered media
Computer Networks: The International Journal of Computer and Telecommunications Networking
EURASIP Journal on Wireless Communications and Networking
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In this paper, an empirically optimized channel-matched quantizer, and a joint stochastic-control based rate controller and channel estimator for H.261 based video transmission over a noisy channel is proposed. The rate controller adaptively learns to choose the correct channel matched quantizer using a stochastic learning algorithm. The stochastic automaton based learning algorithm aids in estimating the channel bit error rate based on a one bit feedback from the decoder. The algorithm is observed to converge to the optimal choice of the quantizer very quickly for various channel bit error probabilities and for different video sequences. When compared to traditional channel estimation schemes the proposed technique has several advantages. First, the proposed method results in a significant reduction in the delay and bandwidth requirement for channel estimation when compared to pilot symbol aided channel estimation schemes. Next, the stochastic learning algorithm used to estimate the channel bit error rate has simple computations. This makes it attractive for low power applications such as wireless video communications. This is in contrast to traditional blind channel estimation schemes that are computationally expensive, in general.