BOUND ON PREDICTOR MISADJUSTMENT IN ADPCM.

K. Sayood; D. C. Farden

BOUND ON PREDICTOR MISADJUSTMENT IN ADPCM.

K. Sayood, D. C. Farden

Electrical & Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

Differential PCM with backward adaptive prediction is a popular technique for data compression. Because of the presence of the quantizer in the feedback loop, the adaptation process has been difficult to analyze. The authors present a bound on the predictor misadjustment and obtain some easily verifiable conditions for convergence of the bound.

Original language	English (US)
Pages (from-to)	1336-1339
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
State	Published - 1987

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Cite this

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title = "BOUND ON PREDICTOR MISADJUSTMENT IN ADPCM.",

abstract = "Differential PCM with backward adaptive prediction is a popular technique for data compression. Because of the presence of the quantizer in the feedback loop, the adaptation process has been difficult to analyze. The authors present a bound on the predictor misadjustment and obtain some easily verifiable conditions for convergence of the bound.",

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year = "1987",

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AU - Sayood, K.

AU - Farden, D. C.

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Y1 - 1987

N2 - Differential PCM with backward adaptive prediction is a popular technique for data compression. Because of the presence of the quantizer in the feedback loop, the adaptation process has been difficult to analyze. The authors present a bound on the predictor misadjustment and obtain some easily verifiable conditions for convergence of the bound.

AB - Differential PCM with backward adaptive prediction is a popular technique for data compression. Because of the presence of the quantizer in the feedback loop, the adaptation process has been difficult to analyze. The authors present a bound on the predictor misadjustment and obtain some easily verifiable conditions for convergence of the bound.

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M3 - Conference article

AN - SCOPUS:0023167979

SN - 0736-7791

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JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

ER -

BOUND ON PREDICTOR MISADJUSTMENT IN ADPCM.

Abstract

ASJC Scopus subject areas

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