DocumentCode
288449
Title
Preprocessing of the input vectors for the linear associator neural networks
Author
Haque, Abul L. ; Cheung, John Y.
Author_Institution
Sch. of Comput. Sci., Oklahoma Univ., Norman, OK, USA
Volume
2
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
930
Abstract
This paper presents a methodology for ensuring the input to the linear associator neural network to be all linearly independent. This is a required condition for the linear associator neural network in order to produce exact output during recall. A number of linear associators may be connected in parallel to increase the capacity. A method to group all the input vectors as a set of linearly independent vectors is presented. The performance of the model is discussed
Keywords
neural nets; input vector preprocessing; linear associator neural networks; Computer science; Data preprocessing; Neural networks; Noise measurement; Signal to noise ratio; Vectors;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICNN.1994.374305
Filename
374305
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