| 4/2013 - 13 |
Linearization of Optimal Compressor Function and Design of Piecewise Linear Compandor for Gaussian SourceNIKOLIC, J.   , PERIC, Z. , ALEKSIC, D. , ANTIC, D. |
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Author keywords
distortion, piecewise linear approximation, quantization, signal to noise ratio
References keywords
quantization(8), nikolic(8), scalar(7), coding(6), adaptive(6), speech(5), quantizer(5), algorithm(5), uniform(4), theory(4)
No common words between the references section and the paper title.
About this article
Date of Publication: 2013-11-30
Volume 13, Issue 4, Year 2013, On page(s): 73 - 78
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.04013
Web of Science Accession Number: 000331461300013
SCOPUS ID: 84890215004
Abstract
The constraints on the quantizer model are usually related to how complex the model can be designed and implemented. For the given bit rate, it is desirable to provide the highest possible signal to quantization noise ratio (SQNR) with reasonable complexity of a quantizer model. In order to avoid the influence of compressor function nonlinearity and the difficulties appearing in implementing and designing, especially in the Gaussian probability density function case, in this paper we linearize the optimal compressor function within the segments. We take advantage of piecewise linearization of the optimal compressor function, as a convenient solution for less complex designing compared to the asymptotically optimal compandor, and we provide performances close to the ones of the asymptotically optimal compandor. This makes our model useful in applications where the design and implementation complexity is a decisive factor. We propose a piecewise linear compandor (PLC) with an equal number of reproduction levels per nonuniformly spaced segments, where the segment thresholds are allotted to the equidistant optimal compressor function values. We study how the number of segments affects SQNR of the PLC. Features of the proposed PLC indicate its theoretical and practical significance in quantization of Gaussian source signals. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
