In this treatise a range of Line Spectrum Frequency (LSF) Vector Quantization (VQ) schemes were studied comparatively, which were designed for wideband speech codecs. Both predictive arrangements and memoryless schemes were investigated. Specifically, both memoryless Split Vector Quantization (SVQ) and Classified Vector Quantization (CVQ) were studied. These techniques exhibit a low complexity ...

In this paper we propose a new technique to quantize the spectral information in an Algebraic Code-Excited Linear Prediction (ACELP) wideband codec. The Voicing-Based Vector Quantization (VBVQ) presented in this paper, optimizes the search of the optimum vector while reducing the codebook entries by almost one third. In the VBVQ training phase, three codebooks are individually designed for voic...

We experimentally assess compression with scalar and vector quantization for fixed-mobile convergent networks. We show that four-dimensional vector quantization allows 73% compression compliant with 3GPP EVM recommendations for transmissions over 25 km SSMF with 1:16 split ratio.

Coding algorithms seek to minimize the bit rate in the digital representation of a signal without an objectionable loss of signal quality in the process. Speech enhancement means improvement in intelligibility and/or quality of a speech signal. This paper deals with multistage vector quantization technique used for coding of narrow band speech signals. The parameter used for coding of speech si...

This paper presents a survey on vector quantization for image compression. Moreover it provides a means of decomposition of the signal in an approach which takes the improvement of inter and intra band correlation as more lithe partition for higher dimension vector spaces. Thus, the image is compressed without information loss using artificial neural networks (ANN). Since 1988, a growing body o...

Transmission of Vector Quantized Images by Self-Organizing Map Jari Kangas Helsinki University of Technology Neural Networks Research Centre Rakentajanaukio 2 C, FIN-02150, Espoo, FINLAND tel: +358 0 451 3275, fax: +358 0 451 3277 email: Jari.Kangas@hut. Abstract Image compression is needed for image storage and transmission applications. Vector quantization methods o er good performance when h...

This thesis is an investigation of Vector Quantization, Scalar Linear Prediction and other related signal processing techniques, with the purpose of providing high quality, low delay speech waveform coding at medium data rates (16 kbls). Speech waveform coding systems based on adaptive scalar prediction and adaptive scalar quantization have been used to provide toll quality coded speech at high...

AND LATTICE VECTOR QUANTIZATION Peter Monta and Shiufun Cheung Advanced Television and Signal Processing Group Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge, MA ABSTRACT We describe a perceptual audio coder that employs nonuniform hierarchical lterbanks and entropy-coded lattice vector quantization. The nonuniform lterbanks present a good match to critical-b...

Vector quantization aims to form new vectors/matrices with shared values close to the original. It could compress data with acceptable information loss, and could be of great usefulness in areas like Image Processing, Pattern Recognition and Machine Learning. In recent years, the importance of quantization has been soaring as it has been discovered huge potentials in deploying practical neural ...

ii ACKNOWLEDGEMENTS If I have seen this far, it is because I have stood on the shoulders of giants.-Sir Isaac Newton I am highly indebted to my advisor, Dr. Sunanda Mitra for providing consistent support and guidance both technically and financially during my Master's program. Her timely suggestions and valuable advice enabled the successful completion of this work. I would also like to thank D...