DocumentCode
3068888
Title
Learning convergence in differential neurocontrol
Author
Frolov, Alexander ; Roschin, Vadim ; Rizek, Stanislav
Author_Institution
Inst. of Higher Nervous Activity & Neurophysiol., Acad. of Sci., Moscow, Russia
fYear
1995
fDate
20-23 Sep 1995
Firstpage
32
Lastpage
38
Abstract
A new method of differential control is based on the analogy with the brain function in visual-motor coordination. The proposed scheme simulates both learning and operation procedures in living creatures. The method does not require calculation of matrix inverses. The model of pseudoinversion of Jacobean is generated as a layered neural network. It is being developed during the learning process based on the error backpropagation algorithm. Its convergence is analyzed in detail for a linear case
Keywords
backpropagation; convergence; neurocontrollers; convergence; differential neurocontrol; error backpropagation algorithm; layered neural network; pseudoinversion; Artificial neural networks; Biological neural networks; Brain modeling; Computer science; Control systems; Convergence; Jacobian matrices; Neurocontrollers; Neurophysiology; Nonlinear control systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Neuroinformatics and Neurocomputers, 1995., Second International Symposium on
Conference_Location
Rostov on Don
Print_ISBN
0-7803-2512-5
Type
conf
DOI
10.1109/ISNINC.1995.480833
Filename
480833
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