Solving the N-bit parity problem using neural networks

被引：23

作者：

Hohil, ME ^{[1
]}

Liu, DR ^{[1
]}

Smith, SH ^{[1
]}

机构：

[1] Stevens Inst Technol, Dept Elect & Comp Engn, Hoboken, NJ 07030 USA

来源：

NEURAL NETWORKS | 1999年 / 12卷 / 09期

基金：

美国国家科学基金会;

关键词：

N-bit parity problem; exclusive-OR problem; neural networks;

D O I：

10.1016/S0893-6080(99)00069-6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this letter, a constructive solution to the N-bit parity problem is provided with a neural network that allows direct connections between the input layer and the output layer. The present approach requires no training and adaptation, and thus it warrants the use of the simple threshold activation function for the output and hidden layer neurons. It is previously shown that this choice of activation function and network structure leads to several solutions for the 3-bit parity problem obtained using linear programming. One of the solutions for the 3-bit parity problem is then generalized to obtain a solution for the N-bit parity problem using [N/2] hidden layer neurons. It is shown that through the choice of a "staircase" type activation function, the [N/2] hidden layer neurons can be further combined into a single hidden layer neuron. (C) 1999 Elsevier Science Ltd. All rights reserved.

引用

页码：1321 / 1323

页数：3