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Convergent algorithms for pattern recognition in nonlinearly evolving nonstationary environment

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1 Author(s)

Blaydon and Ho have recently proposed two algorithms to determine the probability p(A/x) that a sample with the set of attributes x belongs to a pattern class A, assuming a fixed p(A/x). The present letter modifies these algorithms to allow p(A/x) ≡ pi(A/x), i= 1, 2, ..., to evolve (not necessarily linearly) with i. Dynamic stochastic approximation arguments are used.

Published in:

Proceedings of the IEEE  (Volume:56 ,  Issue: 2 )

Date of Publication:

Feb. 1968

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