DocumentCode :
3276670
Title :
Performance analysis and application of the bidirectional associative memory to industrial spectral signatures
Author :
Mathai, G. ; Upadhyaya, B.R.
Author_Institution :
Dept. of Nucl. Eng., Tennessee Univ., Knoxville, TN, USA
fYear :
1989
fDate :
0-0 1989
Firstpage :
33
Abstract :
A detailed study of the performance of the bidirectional associative memory (BAM) for the classification of power spectral density (PSD) functions is presented. The BAM has error-correcting properties and is capable of generating a successful recall, even with noisy and incomplete patterns. Suitable pattern coding schemes are utilized to enhance the discriminating features in the patterns. A bit-mapping scheme is used to construct binary pattern vectors from the PSD. The numerical aspects of signature encoding and fault tolerance property of the BAM are evaluated using spectral density functions of signals from a fiber-manufacturing rotating machinery system. The results of the application of the BAM are superior to those obtained with classical pattern recognition methods.<>
Keywords :
content-addressable storage; neural nets; pattern recognition; spectral analysis; bidirectional associative memory; binary pattern vectors; bit-mapping scheme; discriminating features; error-correcting properties; fault tolerance property; feature enhancement; fiber-manufacturing rotating machinery system; incomplete patterns; industrial spectral signatures; noise; pattern coding schemes; pattern recognition; performance analysis; power spectral density function classification; signature encoding; Associative memories; Neural networks; Pattern recognition; Spectral analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1989. IJCNN., International Joint Conference on
Conference_Location :
Washington, DC, USA
Type :
conf
DOI :
10.1109/IJCNN.1989.118556
Filename :
118556
Link To Document :
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