Cart (Loading....) | Create Account
Close category search window
 

Neural minor component analysis approach to robust constrained beamforming

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Fiori, S. ; Fac. of Eng., Univ. of Perugia, Italy

Since the pioneering work of S.-I. Amari (1977) and E. Oja (1982; 1989; 1992), principal component neural networks and their extensions have become an active adaptive signal processing research field. One of such extensions is minor component analysis (MCA), that proves to be effective in tasks such as robust curve/surface fitting and noise reduction. The aims of the paper are to give a detailed and homogeneous review of one-unit first minor/principal component analysis and to propose an application to robust constrained beamforming. In particular, after a careful presentation of first/minor component analysis algorithms based on a single adaptive neuron, along with relevant convergence/steady-state theorems, it is shown how the adaptive robust constrained beamforming theory by H. Cox et al. (see IEEE Trans. Acoust. Speech. Sig. Process., vol.34, no.3, p.393-8, 1986; vol.35, no.10, p.1365-76, 1987) may be advantageously recast into an MCA setting. Experimental results obtained with a triangular array of microphones introduced in a teleconference context help to assess the usefulness of the proposed theory.

Published in:

Vision, Image and Signal Processing, IEE Proceedings -  (Volume:150 ,  Issue: 4 )

Date of Publication:

22 Aug. 2003

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.