The construction of minimal multilayered perceptrons : a case study for sorting

P.J. Zwietering; E.H.L. Aarts; J. Wessels

doi:10.1016/0925-2312(93)90007-P

The construction of minimal multilayered perceptrons : a case study for sorting

P.J. Zwietering
, E.H.L. Aarts
, J. Wessels

Research output: Contribution to journal › Article › Scientific › peer-review

4 Citations (Scopus)

Abstract

We consider the construction of minimal multilayered perceptrons for solving combinatorial optimization problems. Though general in nature, the proposed construction method is presented as a case study for the sorting problem. The presentation starts with an O((n!)2) three-layered perceptron based on complete enumeration, that solves the sorting problem of n numbers. This network is then gradually reduced to an O(n2) three-layered perceptron, which can be viewed as a neural implementation of Preparata's parallel enumerative sorting algorithm.

Original language	English
Pages (from-to)	197-210
Number of pages	14
Journal	Neurocomputing
Volume	5
Issue number	4-5
DOIs	https://doi.org/10.1016/0925-2312(93)90007-P
Publication status	Published - 1993
Externally published	Yes

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title = "The construction of minimal multilayered perceptrons : a case study for sorting",

abstract = "We consider the construction of minimal multilayered perceptrons for solving combinatorial optimization problems. Though general in nature, the proposed construction method is presented as a case study for the sorting problem. The presentation starts with an O((n!)2) three-layered perceptron based on complete enumeration, that solves the sorting problem of n numbers. This network is then gradually reduced to an O(n2) three-layered perceptron, which can be viewed as a neural implementation of Preparata's parallel enumerative sorting algorithm.",

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AU - Wessels, J.

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AB - We consider the construction of minimal multilayered perceptrons for solving combinatorial optimization problems. Though general in nature, the proposed construction method is presented as a case study for the sorting problem. The presentation starts with an O((n!)2) three-layered perceptron based on complete enumeration, that solves the sorting problem of n numbers. This network is then gradually reduced to an O(n2) three-layered perceptron, which can be viewed as a neural implementation of Preparata's parallel enumerative sorting algorithm.

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DO - 10.1016/0925-2312(93)90007-P

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The construction of minimal multilayered perceptrons : a case study for sorting

Abstract

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