Abstract
In this paper we deal with the problem of approximating the probability density function of a signal by means of adaptive activation function neurons. We compare the proposed approach to the one based on a mixture of kernels and show through computer simulations that comparable results may be obtained with limited expense in computational efforts.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
