Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0925-2312(97)00030-1
Title: On the solution of the parity problem by a single hidden layer feedforward neural network
Authors: Setiono, R. 
Keywords: Feedforward network
Parity problem
Sigmoid function
Issue Date: 1-Sep-1997
Source: Setiono, R. (1997-09-01). On the solution of the parity problem by a single hidden layer feedforward neural network. Neurocomputing 16 (3) : 225-235. ScholarBank@NUS Repository. https://doi.org/10.1016/S0925-2312(97)00030-1
Abstract: It is known that the N-bit parity problem is solvable by a standard feedforward neural network having a single hidden layer consisting of (N/2) + 1 hidden units if N is even and (N + 1)/2 hidden units if N is odd. The network does not allow a direct connection between the input layer and the output layer and the transfer function used in all hidden units and the output unit is the usual sigmoidal function σ(x)-1/(1 + exp(-x)). We show that such a solution can be easily obtained by solving a system of linear equations.
Source Title: Neurocomputing
URI: http://scholarbank.nus.edu.sg/handle/10635/99365
ISSN: 09252312
DOI: 10.1016/S0925-2312(97)00030-1
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

22
checked on Apr 16, 2018

WEB OF SCIENCETM
Citations

20
checked on Apr 16, 2018

Page view(s)

19
checked on Mar 12, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.