29.Information Theory by John G. Webster (Editor)

By John G. Webster (Editor)

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Makhoul, S. Roucos, and H. Gish, Vector quantization in speech coding, Proc. IEEE, 73: 1551–1588, 1985. 14. A. Gersho and R. M. Gray, Vector Quantization and Signal Compression, Norwell, MA: Kluwer, 1992. 15. P. A. Chou, T. Lookabaugh, and R. M. Gray, Entropy-constrained vector quantization, IEEE Trans. , 37: 31–42, 1989. 16. J. Foster, R. M. Gray, and M. O. Dunham, Finite-state vector quantization for waveform coding, IEEE Trans. Inf. Theory, 31: 348–359, 1985. 17. R. L. Baker and R. M. Gray, Differential vector quantization of achromatic imagery, Proc.

Vector quantization is one of the most popular lossy data compression techniques. It is widely used in image, audio, and speech compression applications. The most popular vector quantization is fixed-length vector quantization. In the quantization process, consecutive input samples are grouped into fixed-length vectors first. As an example, we can group L samples of input speech as one L-dimensional vector, which forms the input vector to the vector quantizer. For a typical vector quantizer, both the encoder and the decoder share a common codebook, C ϭ ͕ci; i ϭ 1, .

261: Video Codec for Audiovisual Services at p ϫ 64 kbits/s. ITU-T (CCITT), March 1993. 5. 263: Video Coding for Low Bitrate Communication, ITU-T (CCITT), December 1995. 6. 3 Kbits/s, ITUT (CCITT), October 1995. 7. 728: Coding of Speech at 16 Kbit/s Using Low-Delay Code Excited Linear Prediction (LD-CELP), ITU-T (CCITT), September 1992. 8. R. N. 6–21. 9. R. N. , New York: McGraw-Hill, 1978, pp. 204–215. 10. H. Nyquest, Certain topics in telegraph transmission theory, Trans. AIEE, 47: 617–644, 1928.

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