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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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2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

2021-Jun-06
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  4/2016 - 5

Modified BTC Algorithm for Audio Signal Coding

TOMIC, S. See more information about TOMIC, S. on SCOPUS See more information about TOMIC, S. on IEEExplore See more information about TOMIC, S. on Web of Science, PERIC, Z. See more information about  PERIC, Z. on SCOPUS See more information about  PERIC, Z. on SCOPUS See more information about PERIC, Z. on Web of Science, NIKOLIC, J. See more information about NIKOLIC, J. on SCOPUS See more information about NIKOLIC, J. on SCOPUS See more information about NIKOLIC, J. on Web of Science
 
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Download PDF pdficon (1,399 KB) | Citation | Downloads: 591 | Views: 2,125

Author keywords
adaptive coding, audio compression, correlation, quantization, signal to noise ratio

References keywords
coding(9), audio(6), speech(5), digital(5), signal(4), processing(4), algorithm(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-11-30
Volume 16, Issue 4, Year 2016, On page(s): 31 - 38
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.04005
Web of Science Accession Number: 000390675900005
SCOPUS ID: 85007545486

Abstract
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This paper describes modification of a well-known image coding algorithm, named Block Truncation Coding (BTC) and its application in audio signal coding. BTC algorithm was originally designed for black and white image coding. Since black and white images and audio signals have different statistical characteristics, the application of this image coding algorithm to audio signal presents a novelty and a challenge. Several implementation modifications are described in this paper, while the original idea of the algorithm is preserved. The main modifications are performed in the area of signal quantization, by designing more adequate quantizers for audio signal processing. The result is a novel audio coding algorithm, whose performance is presented and analyzed in this research. The performance analysis indicates that this novel algorithm can be successfully applied in audio signal coding.


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

[1] W. C. Chu, Speech Coding Algorithms: Foundation and Evolution of Standardized Coders. John Wiley & Sons, New Jersey, Chapters 5-6, pp. 143-183, 2003.

[2] L. Hanzo, C. Somerville, J. Woodard, Voice and Audio Compression for Wireless Communications. London, John Wiley & Sons, Chapter 1, pp. 1-28, 2007.

[3] A. Kondoz, Digital Speech: Coding for Low Bit Rate Communication Systems. John Wiley & Sons, Ch. 2-3, pp. 5-55, 2004.

[4] E. J. Delp, O. R. Mithcell, "Image compression using block bruncation coding", IEEE Trans. Commun., vol. 27 no. 9, pp. 1335-1342, 1979.
[CrossRef] [Web of Science Times Cited 494] [SCOPUS Times Cited 696]


[5] Compact Disc Digital Audio System, (IEC/ANSI) CEI-IEC-908, 1987.

[6] P. Ted, A. Spanias, "Perceptual coding of digital audio" Proceedings of the IEEE, vol. 88 no. 4, pp. 451-515, 2000.
[CrossRef] [Web of Science Times Cited 437] [SCOPUS Times Cited 591]


[7] K. Sayood, Introduction to data compression, Newnes, Chapter 1, pp. 3-38, 2012.

[8] M. Bosi, R. Goldberg. Introduction to digital audio coding and standards. Vol. 721. Springer Science & Business Media, Chapter 11-15, pp. 264-425, 2012.

[9] Z. Peric, S. Tomic, M. Tancic, "High quality speech signal coding with the application of BTC algorithm", International Conference on Advanced Technologies, Systems and Services in Telecommunications - TELSIKS, Nis, Serbia, October 2015, pp. 23-26

[10] V. Despotovic, Z. Peric, L. Velimirovic, V. Delic, "DPCM with forward gain-adaptive quantizer and simple switched predictor for high quality speech signals," Advances in Electrical and Computer Engineering, vol.10, no.4, pp.95-98, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 10] [SCOPUS Times Cited 11]


[11] Q. Guoping, "Color image indexing using BTC", IEEE Transactions on Image Processing, vol. 12, no. 1 pp. 93-101, 2003.
[CrossRef] [Web of Science Times Cited 85] [SCOPUS Times Cited 126]


[12] ITU-T, Recommendation G.711, "Pulse Code Modulation (PCM) of Voice Frequencies", International Telecommunication Union, 1972.

[13] 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.

[14] Z. Peric, M. Petkovic, M. Dincic, "Simple compression algorithm for memoryless Laplacian source based on the optimal companding technique", Informatica, vol. 20, no. 1, pp. 99-114, 2009.

[15] N. Judell, L. Scharf, "A simple derivation of Lloyd's classical result for the optimum scalar quantizer", IEEE Trans. Inform. Theory, vol. 32, no. 2, pp. 326-328, 1986.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 17]


[16] S. Jiang, R. Yin, P. Liu, "Finite-state entropy-constrained vector quantiser for audio modified discrete cosine transform coefficients uniform quantisation", IET Signal Processing, vol. 9 , no. 1, pp. 30-36, 2015.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 4]


[17] R. Farias, J. Brossier, "Adaptive quantizers for estimation", Signal Processing, vol. 93, no. 11, pp. 3076-3087, 2013.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 8]


[18] N. S. Jayant, P. Noll, Digital coding of waveforms. New Jersey, Prentice Hall, Chapter 5, pp. 221-251, 1984.

[19] A. Spanias, T. Painter, V. Atti, Audio signal processing and coding, John Wiley & Sons, 2006.

[20] D. Hui, D. Neuhoff, "Asymptotic analysis of optimal fixed-rate uniform scalar quantization", IEEE Trans. Inform. Theory, vol. 47, no. 3, pp. 957-977, 2001.
[CrossRef] [Web of Science Times Cited 67] [SCOPUS Times Cited 83]




References Weight

Web of Science® Citations for all references: 1,121 TCR
SCOPUS® Citations for all references: 1,536 TCR

Web of Science® Average Citations per reference: 53 ACR
SCOPUS® Average Citations per reference: 73 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 2022-05-23 05:11 in 56 seconds.




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