Titlebook: Noise Reduction in Speech Processing; Israel Cohen,Yiteng Huang,Jacob Benesty Book 20091st edition Springer-Verlag Berlin Heidelberg 2009

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Mean-Squared Error Criterion,or (MSE) is, by far, the most used one because of its simplicity in terms of deriving useful filters. This chapter presents relevant error signals from which meaningful MSE criteria are built in the different domains.

PACK

Optimal Filters in the Time Domain,s chapter, we restrict our attention to filters in the time domain. Particularly, much emphasis is on the Wiener filter [125] as it is directly derived from the MSE criterion and most well-known algorithms are somehow related to it.

inferno

Spectral Enhancement Methods,ch and noise signals, and derive estimators for the speech signal using various distortion measures. We also describe an example of a speech enhancement algorithm and demonstrate its performance on speech signals degraded by various additive noise types.

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Problem Formulation,In this chapter, we explain the traditional formulation of the (additive) noise problem and its reduction by linear filtering in the time, frequency, and Karhunen-Loève expansion domains.

Lumbar-Stenosis

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Physiatrist

Israel Cohen,Yiteng Huang,Jacob BenestyOverview of the state of the art of noise reduction algorithms.Concise Treatment

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防锈

amorphous

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