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 Trellis Based Quantization using the BCJR Algorithm. Principle and Application to Correlated Sources
Наименование:

Trellis Based Quantization using the BCJR Algorithm. Principle and Application to Correlated Sources

автор Stephan H. издательство Книга по Требованию Организация здравоохранения
Cтраниц 104        мягкая обложка       
Аннотация:The motivation for this criterion is given by rate-distortion theory as well as by the duality between trellis source encoding and decoding of convolutional channel codes. The approach is based on using vector labels instead of scalar labels on the state transitions. In this work, trellis based source coding using the MAP criterion is described. The comparison to the Viterbi algorithm indicates a superior performance of the TB-BCJR algorithm for short blocks. We present simulation results for encoding of two correlated Gaussian sources using the TB-BCJR algorithm. The tailbiting BCJR algorithm is described and its convergence properties are highlighted. Simulation results reveal that a certain blocklength is required for optimal encoding performance. We explain the idea of using tailbiting sequences to combat the negative e? ects of a ? xed initial state or an explicit storage of the initial state. In addition to that, a way for encoding multiple correlated sources is presented. In order to ensure tailbiting sequences from the symbol-by-symbol output, the path extension method is introduced.
Автор: Stephan H.
Издательство: Книга по Требованию
Год:2010
Цена:
2007 руб
Нет в наличии
Поиск: Trellis Based Quantization using the BCJR Algorithm. Principle and Application to Correlated Sources



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