Continuous-time Hopfield neural network-based optimized solution to 2-channel allocation problem
| Autor: | Zekeriya Uykan |
|---|---|
| Přispěvatelé: | Doğuş Üniversitesi, Mühendislik Fakültesi, Kontrol ve Otomasyon Mühendisliği Bölümü, TR33156, Uykan, Zekeriya |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Continuous-time Hopfield neural network
maxCut problem channel allocation problem Mathematical optimization Optimization problem General Computer Science Channel allocation schemes Artificial neural network Computer science Graph partition Maxcut Problem Channel Allocation Problem Continuous-Time Hopfield Neural Network Hopfield network Matrix (mathematics) Electric power system Standard algorithms Electrical and Electronic Engineering |
| Zdroj: | Volume: 23, Issue: 2 480-490 Turkish Journal of Electrical Engineering and Computer Science |
| ISSN: | 1300-0632 1303-6203 |
| Popis: | Uykan, Zekeriya (Dogus Author) The channel allocation problem in cellular radio systems is NP-complete, and thus its general solution is not known for even the 2-channel case. It is well known that the link gain system matrix (or received-signal power system matrix) of the radio network is (and may be highly) asymmetric, and that as the Hopfield neural network is applied to optimization problems, its weight matrix should be symmetric. The main contribution of this paper is as follows: turning the channel allocation problem into a maxCut graph partitioning problem, we propose a simple and effective continuous-time Hopfield neural network-based solution by determining its symmetric weight matrix from the asymmetric received-signal-power-system matrix. Computer simulations confirm the effectiveness and superiority of the proposed solution as compared to standard algorithms for various illustrative cellular radio scenarios for the 2-channel case. |
| Databáze: | OpenAIRE |
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