By Jacob Benesty, Yiteng Huang
By adaptive sign processing, we suggest, mostly, adaptive ?ltering.In- identified environments the place we have to version, determine, or song time-varying channels, adaptive ?ltering has been confirmed to be an e?ective and strong device. accordingly, this device is now in use in lots of di?erent ?elds. because the invention, through Widrow and Ho? in 1959, of 1 of the ?rst advert- tive ?lters, the so-called least-mean-square, many functions seemed to have the aptitude to exploit this basic inspiration. 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 subtle adaptive algorithms turned noticeable as real-world difficulties are extra advanced and extra hard. even if the idea of adaptive ?ltering is already a well-established subject in sign processing, new and more suitable options are came across each year through researchers. a few of these contemporary ways are mentioned during this booklet. The target of this publication is to supply, for the ?rst time, a connection with the most well liked real-world purposes the place adaptive ?ltering recommendations play an enormous position. to take action, we invited best researchers in di?erent ?elds to c- tribute chapters addressing their speci?c subject of analysis. millions of pages wouldprobablynotbe enoughto describeallthe practicalapplicationsutil- ing adaptive algorithms. accordingly, we restricted the themes to a few vital functions in acoustics, speech, instant, and networking, the place examine continues to be very energetic and open.
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Additional resources for Adaptive Signal Processing: Applications to Real-World Problems
Huang and J. Benesty, “Adaptive multi-channel least mean square and Newton algorithms for blind channel identiﬁcation,” Signal Processing, vol. 82, pp. 1127–1138, Aug. 2002. 13. D. R. Morgan, J. Benesty, and M. M. , vol. 5, no. 7, pp. 174–176, July 1998. 2 Adaptive Feedback Cancellation in Hearing Aids James M. com Abstract. In feedback cancellation in hearing aids, an adaptive ﬁlter is used to model the feedback path. The output of the adaptive ﬁlter is subtracted from the microphone signal to cancel the acoustic and mechanical feedback picked up by the microphone, thus allowing more gain in the hearing aid.
49, pp. 1208- 1215, June 2001. 22 J. Benesty et al. 7. D. R. Morgan and S. G. , vol. 3, pp. 245–247, Aug. 1996. 8. S. Amari, “Natural gradient works eﬃciently in learning,” Neural Computation, vol. 10, pp. 251–276, Feb. 1998. 9. J. Benesty and S. L. Gay, “An improved PNLMS algorithm,” in Proc. IEEE ICASSP, 2002. 10. R. K. Martin, W. A. Sethares, R. C. Williamson, and C. R. , “Exploiting sparsity in adaptive ﬁlters,” in Conference on Information Sciences and Systems, The John Hopkins University, 2001.
An eﬀective approach that does not reduce the hearing aid gain is constrained adaptation , which has been developed to allow for adaptation to changes in the feedback path while reducing processing artifacts. The ﬁltered-X algorithm ,  is also an eﬀective approach for reducing the sensitivity of the feedback cancellation system to low-frequency inputs while allowing for rapid adaptation to feedback-path changes at high frequencies. The amount of gain possible in a hearing aid is ultimately limited by the ability of the feedback cancellation system to model the actual feedback path.