Research Journal of Applied Sciences
ISSN: Online 1993-6079ISSN: Print 1815-932x
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. Approximation by Regular Neural Networks in Terms of Dunkl Transform.
DOI: https://doi.org/10.36478/rjasci.2016.933.941
URL: https://www.makhillpublications.co/view-article/1815-932x/rjasci.2016.933.941