Research Journal of Applied Sciences

Year: 2016
Volume: 11
Issue: 10
Page No. 933 - 941

Approximation by Regular Neural Networks in Terms of Dunkl Transform

Authors : Eman Bhaya and Omar Al-sammak

Abstract: Dunkl operator here we introduce a modified version of and use it to prove a theorem shows that functionals and rth order modulus of smoothness in K-theorem shows thatare equivalent. We use this equivalence to introduce p<1 spaces for Lp (K) essential degree of approximation using regular neural networks p and how a multivariate function in spaces for can be approximated using a p<1 spaces for Lp (K) multivariate p function in forward regular neural network. So, we can have the essential approximation using regular FFN. P<1 spaces for Lp (K) ability of a multivariate function in spaces for using regular FFN.

How to cite this article:

Eman Bhaya and Omar Al-sammak, 2016. Approximation by Regular Neural Networks in Terms of Dunkl Transform. Research Journal of Applied Sciences, 11: 933-941.

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