Journal ArticleDOI
Systolic architectures for vector quantization
TLDR
A family of architectural techniques are proposed which offer efficient computation of weighted Euclidean distance measures for nearest-neighbor codebook searching and very high vector-quantization (VQ) throughout can be achieved for many speech and image-processing applications.Abstract:
A family of architectural techniques are proposed which offer efficient computation of weighted Euclidean distance measures for nearest-neighbor codebook searching. The general approach uses a single metric comparator chip in conjunction with a linear array of inner product processor chips. Very high vector-quantization (VQ) throughout can be achieved for many speech and image-processing applications. Several alternative configurations allow reasonable tradeoffs between speed and VLSI chip area required. >read more
Citations
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Journal ArticleDOI
Competitive learning algorithms for vector quantization
TL;DR: A new competitive-learning algorithm based on the “conscience” learning method is introduced that is shown to be efficient and yields near-optimal results in vector quantization for data compression.
Journal ArticleDOI
Neural networks for vector quantization of speech and images
TL;DR: The authors show how a collection of neural units can be used efficiently for VQ encoding, with the units performing the bulk of the computation in parallel, and describe two unsupervised neural network learning algorithms for training the vector quantizer.
Journal ArticleDOI
Variable rate vector quantization for speech, image, and video compression
TL;DR: Three variable-rate vector quantizer systems are applied to speech, image, and video sources and compared to standard vector quantization and noiseless variable- rate coding approaches, providing significant performance improvements for subband speech coding, predictive image coding, and motion-compensated video.
Journal ArticleDOI
Bit-serial VLSI implementation of vector quantizer for real-time image coding
P.A. Ramamoorthy,B. Potu,T. Tran +2 more
TL;DR: A practical high-throughput architecture and its implementation for real-time coding of television-quality signals are presented and the architecture is directed toward the implementation of multistage vector quantization (VQ), as the authors' simulation results show that the latter is more suitable for real -time coding.
Journal ArticleDOI
Multiplication free vector quantization using L/sub 1/ distortion measure and its variants
TL;DR: A gradient-based approach for codebook design that does not require any multiplications or median computation is proposed and the viability of multiplication-free predictive vector quantization of image data is demonstrated.
References
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Journal ArticleDOI
An Algorithm for Vector Quantizer Design
Y. Linde,A. Buzo,Robert M. Gray +2 more
TL;DR: An efficient and intuitive algorithm is presented for the design of vector quantizers based either on a known probabilistic model or on a long training sequence of data.
Journal Article
Vector quantization
TL;DR: During the past few years several design algorithms have been developed for a variety of vector quantizers and the performance of these codes has been studied for speech waveforms, speech linear predictive parameter vectors, images, and several simulated random processes.
Journal ArticleDOI
Why systolic architectures
TL;DR: The basic principle of systolic architectures is reviewed and it is explained why they should result in cost-effective, highperformance special-purpose systems for a wide range of problems.
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.