DocumentCode :
2650933
Title :
A feedforward network of learning automata for pattern classification
Author :
Thathachar, M. A L ; Phansalkar, V.V.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India
fYear :
1991
fDate :
18-21 Nov 1991
Firstpage :
2265
Abstract :
A model made of units of teams of learning automata is developed for the three layer pattern classifier. The algorithm is approximated by an ordinary differential equation (ODE), using weak convergence methods. The pattern recognition problem is posed as a constrained maximization problem. It is shown that the zeros of the ODE correspond to points satisfying first order necessary conditions of the maximization problem. Partial results are obtained showing that the ODE, and hence the algorithm, converge to the local maxima of the maximization problem
Keywords :
automata theory; differential equations; learning systems; neural nets; optimisation; pattern recognition; constrained maximization; feedforward network; learning automata; local maxima; ordinary differential equation; pattern classification; pattern recognition; three layer pattern classifier; weak convergence; Bismuth; Broadcasting; Convergence; Learning automata; Pattern classification; Pattern recognition; Piecewise linear approximation; Piecewise linear techniques; Signal generators; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
Type :
conf
DOI :
10.1109/IJCNN.1991.170725
Filename :
170725
Link To Document :
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