Titlebook: Real-Time Adaptive Concepts in Acoustics; Blind Signal Separat Daniel W. E. Schobben Book 2001 Springer Science+Business Media Dordrecht 20

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A Blind Signal Separation Algorithmw blind signal separation algorithm is derived which is entirely based on second order statistics. The algorithm can run in off-line or online (adaptive) mode. One of the advantages of this algorithm is that no assumptions are made about the probability density functions or other properties of the s

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elates to the fact that there are no reference signals forthe source signals and also that the mixing system is unknown. Thisbook presents a new method for blind signal separation, which isdeveloped to work on microphone signals. .Acoustic Echo Cancellation (AEC) is a well-known technique to suppres

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Blind Signal Separation Algorithm Evaluationata that is available such that researches can compare their results. Although this chapter is focussed on acoustic applications, many of the remarks apply to other BSS application areas as well. The work in this chapter is published in Schobben eta!.,1999..

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Introduction techniques. Background information on room acoustics, speech and microphone setups is presented. Also the objectives of the work in this book are discussed and an overview of the remaining chapters is given. The chapter concludes with describing the mathematical notation that is used throughout.

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An Efficient Adaptive Filter Implementationonvergence can be extremely slow however when working with real-life audio signals and long filters. Moreover, the computational complexity grows linearly with the filter length making it impractical to implement long (thousands of coefficients) filters in real-time.

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Conclusionstistics. In addition, efficient implementations are presented for the single channel echo canceler and the delay and sum beamformer. Also, methods to evaluate blind signal separation algorithms are given along with comments on what cases are difficult for blind signal separation algorithms.