Adaptive Signal Processing: Applications to Real-World by Jacob Benesty, Yiteng Huang

By Jacob Benesty, Yiteng Huang

By adaptive sign processing, we suggest, usually, adaptive ?ltering.In- identified environments the place we have to version, determine, or tune time-varying channels, adaptive ?ltering has been confirmed to be an e?ective and robust software. accordingly, this software is now in use in lots of di?erent ?elds. because the invention, via Widrow and Ho? in 1959, of 1 of the ?rst advert- tive ?lters, the so-called least-mean-square, many functions looked as if it would have the aptitude to take advantage of this primary suggestion. whereas the variety of - plications (using adaptive algorithms) has been (and retains) ?ourishing with time, because of a number of successes, the necessity for extra refined adaptive algorithms grew to become visible as real-world difficulties are extra advanced and extra hard. even supposing the idea of adaptive ?ltering is already a well-established subject in sign processing, new and more suitable strategies are stumbled on each year by means of researchers. a few of these fresh techniques are mentioned during this e-book. The aim of this booklet is to supply, for the ?rst time, a connection with the most popular real-world purposes the place adaptive ?ltering ideas play an immense function. to take action, we invited best researchers in di?erent ?elds to c- tribute chapters addressing their speci?c subject of research. hundreds of thousands of pages wouldprobablynotbe enoughto describeallthe practicalapplicationsutil- ing adaptive algorithms. as a result, we constrained the themes to a few vital functions in acoustics, speech, instant, and networking, the place study remains to be very lively and open.

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Extra info for Adaptive Signal Processing: Applications to Real-World Problems

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The correlation between the input and output signals of the hearing aid for a narrowband excitation leads to a bias in the adaptive solution unless adequate delay is provided in the hearingaid processing [4], [15]. Frequency-domain adaptive algorithms can also be used for feedback cancellation without a probe signal [16], [17], [9]. The block delay provided by frequency-domain processing using the short-time Fourier transform provides the input-output signal decorrelation needed for the convergence of the feedback cancellation in these systems.

1985. 2. S. Haykin, Adaptive Filter Theory. , 2002. 3. J. Kivinen and M. K. Warmuth, "Exponentiated gradient versus gradient desee nt for linear predietors," In/orm. , vol. 132, pp. 1- 64, Jan. 1997. 4. J. Benesty, T. Gänsler, D. R. Morgan , M . M. Sondhi, and S. L. Gay, Advances in Network and Acoustic Echo cancellation. Springer-Verlag, Berlin, 2001. 5. D. L. Duttweiler, "Proportionate normalized least me an square adaptation in eeho eaneelers," IEEE Trans . Speech Audio Processing, vol. 8, pp.

This constraint requires that the physical feedback path transfer function be known at all times. However, the only information available during adaptation comprises the feedback cancellation filter coefficients and the hearing-aid gain. Further information is supplied by performing an initialization during the hearing-aid fitting; the initialization provides a reference set of adaptive filter coefficients obtained under controlled conditions. The reference set of coefficients can be determined by letting the system adapt in the presence of a white noise source until the adaptive filter coefficients reach steady state, or it can be determined using the system identification procedures described in Sect.

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