Title :
Noise canceling with autoassociative memory trained by order statistics
Author :
Bae, Jinsoo ; Ryu, Young Kwon ; Song, Iickho
Author_Institution :
Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Daejon, South Korea
fDate :
27 Jun-2 Jul 1994
Abstract :
In this paper, noise canceling using an autoassociative memory is considered for possible applications to constant signal detection. The authors use order statistics to help the neural network learn the noise characteristics. In essence, the performance of this neural network is shown to not depend on the distribution of noise, based on simulations for six well known noise probability density functions
Keywords :
content-addressable storage; learning (artificial intelligence); neural nets; noise; probability; signal detection; statistics; autoassociative memory; noise canceling; noise characteristics; order statistics; signal detection; Filters; Gaussian noise; Neural networks; Noise cancellation; Noise figure; Noise reduction; Probability density function; Signal detection; Statistical distributions; Statistics;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374788
