Journal ArticleDOI
Backward adaptive lattice and transversal predictors in low-delay CELP coders
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TLDR
A trade-off among robustness in noisy channels, performance under error-free conditions and computational complexity leads to the residual-driven lattice as an attractive algorithm to be used in LD-CELP structures.About:
This article is published in Signal Processing.The article was published on 1994-09-01. It has received 0 citations till now. The article focuses on the topics: Code-excited linear prediction & Weighting filter.read more
References
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Proceedings ArticleDOI
Code-excited linear prediction(CELP): High-quality speech at very low bit rates
Manfred R. Schroeder,B. S. Atal +1 more
TL;DR: A code-excited linear predictive coder in which the optimum innovation sequence is selected from a code book of stored sequences to optimize a given fidelity criterion, indicating that a random code book has a slight speech quality advantage at low bit rates.
Journal ArticleDOI
Lattice filters for adaptive processing
TL;DR: This paper presents a tutorial review of lattice structures and their use for adaptive prediction of time series, and it is shown that many of the currently used lattice methods are actually approximations to the stationary least squares solution.
Journal ArticleDOI
Product code vector quantizers for waveform and voice coding
M. J. Sabin,Robert M. Gray +1 more
TL;DR: Several algorithms are presented for the design of shape-gain vector quantizers based on a traning sequence of data or a probabilistic model, and their performance is compared to that of previously reported vector quantization systems.
Journal ArticleDOI
A class of all-zero lattice digital filters: Properties and applications
TL;DR: In this paper, a class of minimum- or maximum-phase all-zero lattice digital filters, based on the two-multiplier lattice of Itakura and Saito, is developed.
Journal ArticleDOI
Adaptive filtering with binary reinforcement
TL;DR: It is proved for the binary reinforcement algorithm that the tap weight vector converges in distribution to a random vector that is suitably concentrated about the optimal value based on a least mean-absolute error cost function.
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