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
Citation: 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

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