Minimizing interference in satellite communications using transiently chaotic neural networks

Wen Liu; Lipo Wang

doi:10.1016/j.camwa.2008.10.026

Minimizing interference in satellite communications using transiently chaotic neural networks

Wen Liu, Lipo Wang^*

^*Corresponding author for this work

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

8 Citations (Scopus)

Abstract

The frequency assignment problem (FAP) in satellite communications is solved with transiently chaotic neural networks (TCNN). The objective of this optimization problem is to minimize cochannel interference between two satellite systems by rearranging the frequency assignments. For an N-carrier-M-segment FAP problem, we construct a TCNN consisting of N × M neurons. The performance of the TCNN is demonstrated through solving a set of benchmark problems, where the TCNN finds comparative if not better solutions as compared to the existing algorithms.

Original language	English
Pages (from-to)	1024-1029
Number of pages	6
Journal	Computers and Mathematics with Applications
Volume	57
Issue number	6
DOIs	https://doi.org/10.1016/j.camwa.2008.10.026
Publication status	Published - Mar 2009
Externally published	Yes

Keywords

FAP
Neural network
Optimization
Satellite communications

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10.1016/j.camwa.2008.10.026

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abstract = "The frequency assignment problem (FAP) in satellite communications is solved with transiently chaotic neural networks (TCNN). The objective of this optimization problem is to minimize cochannel interference between two satellite systems by rearranging the frequency assignments. For an N-carrier-M-segment FAP problem, we construct a TCNN consisting of N × M neurons. The performance of the TCNN is demonstrated through solving a set of benchmark problems, where the TCNN finds comparative if not better solutions as compared to the existing algorithms.",

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AU - Wang, Lipo

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AB - The frequency assignment problem (FAP) in satellite communications is solved with transiently chaotic neural networks (TCNN). The objective of this optimization problem is to minimize cochannel interference between two satellite systems by rearranging the frequency assignments. For an N-carrier-M-segment FAP problem, we construct a TCNN consisting of N × M neurons. The performance of the TCNN is demonstrated through solving a set of benchmark problems, where the TCNN finds comparative if not better solutions as compared to the existing algorithms.

KW - FAP

KW - Neural network

KW - Optimization

KW - Satellite communications

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M3 - Article

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JF - Computers and Mathematics with Applications

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ER -

Minimizing interference in satellite communications using transiently chaotic neural networks

Abstract

Keywords

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