Multirate systems and filter banks
Multirate systems and filter banks
Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise
Algebraic Methods for Signal Processing and Communication Coding
Algebraic Methods for Signal Processing and Communication Coding
Quantized Frame Expansions as Source Channel Codes for Erasure Channels
DCC '99 Proceedings of the Conference on Data Compression
Oversampled filter banks: Optimal noise shaping, design freedom, and noise analysis
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 3 - Volume 3
Quantized Oversampled Filter Banks with Erasures
DCC '01 Proceedings of the Data Compression Conference
IEEE Transactions on Signal Processing
Efficient algorithms for burst error recovery using FFT and othertransform kernels
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Performance analysis and recursive syndrome decoding of DFT codes for bursty erasure recovery
IEEE Transactions on Signal Processing
Frame-theoretic analysis of DFT codes with erasures
IEEE Transactions on Signal Processing
Decoding real-number convolutional codes: change detection, Kalman estimation
IEEE Transactions on Information Theory
Decoding real block codes: activity detection Wiener estimation
IEEE Transactions on Information Theory
Filter bank frame expansions with erasures
IEEE Transactions on Information Theory
Optimal filter banks for multiple description coding: analysis and synthesis
IEEE Transactions on Information Theory
Joint source-channel turbo decoding of entropy-coded sources
IEEE Journal on Selected Areas in Communications
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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.