Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Joint Source-Channel Coding by Means of an Oversampled Filter Bank Code | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 82023 Pages 1-12 DOI ASP 2006 82023 Joint Source-Channel Coding by Means of an Oversampled Filter Bank Code Slavica Marinkovicand Christine Guillemot IRISA-INRIA Campus de Beaulieu 35042 Rennes Cedex France Received 1 September 2004 Revised 5 April 2005 Accepted 7 April 2005 Quantized frame expansions based on block transforms and oversampled filter banks OFBs have been considered recently as joint source-channel codes JSCCs for erasure and error-resilient signal transmission over noisy channels. In this paper we consider a coding chain involving an OFB-based signal decomposition followed by scalar quantization and a variable-length code VLC or a fixed-length code FLC . This paper first examines the problem of channel error localization and correction in quantized OFB signal expansions. The error localization problem is treated as an M-ary hypothesis testing problem. The likelihood values are derived from the joint pdf of the syndrome vectors under various hypotheses of impulse noise positions and in a number of consecutive windows of the received samples. The error amplitudes are then estimated by solving the syndrome equations in the least-square sense. The message signal is reconstructed from the corrected received signal by a pseudoinverse receiver. We then improve the error localization procedure by introducing a per-symbol reliability information in the hypothesis testing procedure of the OFB syndrome decoder. The per-symbol reliability information is produced by the soft-input soft-output SISO VLC FLC decoders. This leads to the design of an iterative algorithm for joint decoding of an FLC and an OFB code. The performance of the algorithms developed is evaluated in a wavelet-based image coding system. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION Various joint source-channel coding approaches guided by an optimum .
