A novel signal-processing strategy for hearing-aid design: neurocompensation-Reference-Cited by-同舟云学术

A novel signal-processing strategy for hearing-aid design: neurocompensation

Published:2004-07 Issue:7 Volume:84 Page:1239-1253
ISSN:0165-1684
Container-title:Signal Processing
language:en
Short-container-title:Signal Processing

Author:

Bondy Jeff,Becker Sue,Bruce Ian,Trainor Laurel,Haykin Simon

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference39 articles.

1. D.V. Anderson, Model based development of a hearing aid, Master's Thesis, Brigham Young University, Provo, Utah, April 1994.

2. Evaluation of a hearing compensation algorithm;Anderson;IEEE,1995

3. ANSI, ANSI S3.5-1997, Methods for Calculation of the Speech Intelligibility Index, American National Standards Institute, New York, 1997.

4. S. Becker, I.C. Bruce, Neural coding in the auditory periphery: insights from physiology and modeling lead to a novel hearing compensation algorithm, in: Workshop on Neural Information Coding, Les Houches France, March 2002.

5. A. Bia, Alopex-b: a new, simpler but yet faster version of the alopex training algorithm (Special Issue on Non-gradient Optimization Methods), Internat. J. Neural Systems (2001) 497–507.

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