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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2020 - 2

Gaussian Source Coding using a Simple Switched Quantization Algorithm and Variable Length Codewords

PERIC, Z. See more information about PERIC, Z. on SCOPUS See more information about PERIC, Z. on IEEExplore See more information about PERIC, Z. on Web of Science, PETKOVIC, G. See more information about  PETKOVIC, G. on SCOPUS See more information about  PETKOVIC, G. on SCOPUS See more information about PETKOVIC, G. on Web of Science, DENIC, B. See more information about  DENIC, B. on SCOPUS See more information about  DENIC, B. on SCOPUS See more information about DENIC, B. on Web of Science, STANIMIROVIC, A. See more information about  STANIMIROVIC, A. on SCOPUS See more information about  STANIMIROVIC, A. on SCOPUS See more information about STANIMIROVIC, A. on Web of Science, DESPOTOVIC, V. See more information about  DESPOTOVIC, V. on SCOPUS See more information about  DESPOTOVIC, V. on SCOPUS See more information about DESPOTOVIC, V. on Web of Science, STOIMENOV, L. See more information about STOIMENOV, L. on SCOPUS See more information about STOIMENOV, L. on SCOPUS See more information about STOIMENOV, L. on Web of Science
 
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Download PDF pdficon (1,293 KB) | Citation | Downloads: 180 | Views: 242

Author keywords
Gaussian distribution, quantization, source coding, signal processing algorithms, signal to noise ratio

References keywords
source(8), coding(8), speech(7), signal(7), gaussian(7), quantization(6), scalar(5), quantizers(5), logarithmic(5), optimal(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2020-11-30
Volume 20, Issue 4, Year 2020, On page(s): 11 - 18
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.04002
Web of Science Accession Number: 000594393400002
SCOPUS ID: 85098140347

Abstract
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This paper introduces an algorithm based on switched scalar quantization utilizing a novel -law quantization model (optimized in terms of minimal distortion) and variable length codewords, for high-quality encoding of the signals modeled by Gaussian distribution. The implemented -law quantizer represents an improvement of the standard -law quantizer in terms of bit rate, at the same time providing the equal signal quality. The main concept of the algorithm is to divide the range of the input signal variances into a certain number of sub-ranges, and to design the optimal quantizer for each sub-range. The signal is processed frame-by-frame, and for each frame the best performing quantizer is chosen, where the estimated frame variance is used as the switching criterion. Theoretical results indicate that the proposed algorithm achieves performance comparable to the standard -law quantizer, enabling the compression of about 0.5 bit/sample. The simulation results are provided to confirm the correctness of the proposed model.


References | Cited By  «-- Click to see who has cited this paper

[1] N. S. Jayant, P. Noll, Digital Coding of Waveforms: Principles and Applications to Speech and Video. New Jersey, Prentice Hall, Chapter 4, pp. 115-188, 1984.

[2] K. Sayood, Introduction to Data Compression. San Francisco, Elsevier Science, Chapter 9, pp. 227-270, 2005.
[CrossRef] [SCOPUS Times Cited 291]


[3] D. Salomon, "Variable-length codes for data compression,". London, Springer, Chapter 1, pp. 9-69, 2007.
[CrossRef] [SCOPUS Times Cited 71]


[4] W. C. Chu, "Speech Coding Algorithms: Foundation and evolution of standardized coders," New Jersey, John Wiley & Sons, Chapter 5, pp. 143-158, 2003.
[CrossRef]


[5] Z. Peric, B. Denic, V. Despotovic, "Three-level delta modulation with second-order prediction for Gaussian source coding," Advances in Electrical and Computer Engineering, vol. 18, no. 3, pp. 73-78, 2018.
[CrossRef] [Full Text] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]


[6] J. Nikolic, Z. Peric, A. Jovanovic, "Two forward adaptive dual-mode companding scalar quantizers for Gaussian source," Signal Processing, vol. 120, pp. 129-140, 2016.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 11]


[7] J. Nikolic, Z. Peric, D. Aleksic, D. Antic, "Linearization of optimal compressor function and design of piecewise linear compandor for Gaussian source," Advances in Electrical and Computer Engineering, vol. 13, no. 4, pp. 73-78, 2013.
[CrossRef] [Full Text] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[8] A. D. Lyon, "The u-law CODEC," Journal of Object Technology, vol. 7, no. 8, pp. 17-31, 2008.
[CrossRef] [SCOPUS Times Cited 2]


[9] S. Tomic, Z. Peric, J. Nikolic, "Modified BTC algorithm for audio signal coding," Advances in Electrical and Computer Engineering, vol. 16, no.4, pp. 31-38, 2016.
[CrossRef] [Full Text] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]


[10] Z. Peric, M. Dincic, D. Denic, A. Jocic, "Forward adaptive logarithmic quantizer with new lossless coding method for Laplacian source," Wireless Personal Communications, vol. 59, pp. 625-641, 2010.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 15]


[11] G. K. Venayagamoorthy, W. Zha, "Comparison of nonuniform optimal quantizer designs for speech coding with adaptive critics and particle swarm," IEEE Transactions on Industry Applications, vol. 43, no. 1, pp. 238-244, 2007.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 19]


[12] M. Rahali, H. Loukil, M. S. Bouhlel, "New image compression method using logarithmic quantization," in Proc. Int. Conf. on Information and Digital Technologies (IDT), Hammamet, Tunisia, 2016.
[CrossRef] [SCOPUS Times Cited 4]


[13] M. Mounir, M. B. El_Mashade, "On the selection of the best companding technique for PAPR reduction in OFDM systems," Journal of Information and Telecommunication, vol. 3, no. 3, pp. 400-411, 2019.
[CrossRef]


[14] Z. Ting, L. Junmin, "Robust iterative learning control of multi-agent systems with logarithmic quantizer," in Proc. 34th Chinese Control Conference (CCC), Hangzhou, China , 2015.
[CrossRef] [SCOPUS Times Cited 6]


[15] M. Dincic, Z. Peric, D. Denic, Z. Stamenkovic, "Design of robust quantizers for low-bit analog-to-digital converters for Gaussian source," Journal of Circuits, Systems and Computers, vol. 28, no. supp01, 1940002, 2019.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]


[16] T. Ueki, K. Iwai, T. Matsubara, T. Kurokawa, "Learning accelerator of deep neural networks with logarithmic quantization," in Proc. 7th Int. Congress on Advanced Applied Informatics (IIAI-AAI), Yonago, Japan, 2018.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]


[17] S. Gazor, W. Zhang, "Speech probability distribution," IEEE Signal Process. Letters, vol. 10, no. 7, pp. 204-207, 2003.
[CrossRef] [Web of Science Times Cited 177] [SCOPUS Times Cited 221]


[18] Y. Hou, G. Liu, Q. Wang, W. Xiang, "Performance optimization of digital spectrum analyzer with Gaussian input signal," IEEE Signal Processing Letters, vol. 20, no. 1, pp. 31-34, 2013.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 8]


[19] R. Banner, Y. Nahshan, E. Hoffer, D. Soudry, "Analytical clipping for integer quantization of neural networks," arXiv2018, arXiv: 1810.05723.

[20] G. Petkovic, Z. Peric, L. Stoimenov, "Switched scalar optimal u-law quantization with adaptation performed to both the variance and the distribution of speech signal," Elektronika ir Elektrotechnika, vol. 22, no. 1, pp. 64-67, 2016.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 5]


[21] N. Vucic, Z. Peric, G. Petkovic, "Design of switched quantizers and speech coding based on quasi-logarithmic compandor," Elektronika Ir Elektrotechnika, vol. 24, no. 6, pp. 82-86, 2018.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]


[22] A. Mosic, Z. Peric, M. Savic, S. Panic, "Switched semilogarithmic quantization of Gaussian source with low delay," Elektronika ir Elektrotechnika, vol. 108, no. 2, pp. 71-74, 2011.
[CrossRef]


[23] S. Na, D. Neuhoff, "On the support of MSE-optimal fixed-rate scalar quantizers," IEEE Transactions on Information Theory, vol. 47, no. 7, pp. 2972-2982, 2001.
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 51]


[24] S. Na, "On the support of fixed-rate minimum mean-squared error scalar quantizers for a Laplacian source," IEEE Transactions on Information Theory, vol. 50, no. 5, pp. 937-944, 2004.
[CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 39]


[25] S. Na, "Asymptotic formulas for variance-mismatched fixed-rate scalar quantization of a Gaussian source," IEEE Transactions on Signal Processing, vol. 59, no. 5, pp. 2437-2441, 2011.
[CrossRef] [Web of Science Times Cited 30] [SCOPUS Times Cited 32]


[26] J. Nikolic, Z. Peric, "Lloyd-Max's algorithm implementation in speech coding algorithm based on forward adaptive technique," Informatica, vol. 19, no. 2, pp. 255-270, 2008.



References Weight

Web of Science® Citations for all references: 346 TCR
SCOPUS® Citations for all references: 786 TCR

Web of Science® Average Citations per reference: 13 ACR
SCOPUS® Average Citations per reference: 29 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-02-28 16:02 in 158 seconds.




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