Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/18828
Title: Solving optimization problems in communications using neural networks
Authors: Liu, Wen
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies
Issue Date: 2008
Source: Liu, W. (2008). Solving optimization problems in communications using neural networks. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: The development of communication engineering (Internet, satellites, mobiles) changes our daily life. The optimization problems in communications have motivated research in computational intelligence techniques these years. To improve neural network algorithms for the shortest path routing problem (SPRP), we propose a solution approach using a noisy Hopfield neural network (NHNN) by adding decaying stochastic noise to the continuous Hopfield neural network (HNN). We also improve the energy function for the SPRP. Simulation results show that our approach offers further improvements on route optimality rate compared to other algorithm that employ the HNN.
URI: https://hdl.handle.net/10356/18828
DOI: 10.32657/10356/18828
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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