Scheduled System Maintenance:
On May 6th, system maintenance will take place from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). During this time, there may be intermittent impact on performance. We apologize for the inconvenience.
By Topic

Karhunen-Loeve transform using neural networks

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.

The purchase and pricing options are temporarily unavailable. Please try again later.
3 Author(s)
Xianing Zhu ; Ocron Inc., Santa Clara, CA, USA ; Shengwei Zhang ; Constantinides, A.G.

The optimality of Karhunen-Loeve transform (KLT) over other transforms has been well known, together with the difficulty in implementing practical KLT systems. The wide applications of the transform deserve a new investigation on realizing such systems by using artificial neural networks. In this paper the KLT is known to be equivalent to a constrained optimization problem by maximizing covariance of output signals with the constraint of orthonormality. A neural network is then developed which can converge to the basis vectors of the transform

Published in:

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:7 )

Date of Conference:

27 Jun-2 Jul 1994