基于混沌神經(jīng)網(wǎng)絡(luò)的移動(dòng)通信信道分配方法研究
Channel Assignment Strategy in Mobile Communication Based on Chaos Neural Network
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摘要: 該文應(yīng)用混沌神經(jīng)網(wǎng)絡(luò)求解信道分配問題,給出了信道分配的能量函數(shù)表達(dá)式和混沌神經(jīng)網(wǎng)絡(luò)模型,研究了判別混沌神經(jīng)網(wǎng)絡(luò)混沌特性的Lyapunov指數(shù)法,討論了網(wǎng)絡(luò)模型參數(shù)對(duì)網(wǎng)絡(luò)混沌特性的影響,提出了基于混沌神經(jīng)網(wǎng)絡(luò)的信道分配算法.仿真結(jié)果表明,混沌神經(jīng)網(wǎng)絡(luò)具有復(fù)雜的瞬態(tài)混沌特性,它比Hopfield網(wǎng)絡(luò)具有更強(qiáng)的搜索全局最優(yōu)解的能力,和更快的收斂速度.Abstract: Chaos Neural Network（CNN）is applied to solve channel assignment problem in this paper. Energy function expression of channel assignment as well as mathematic model of CNN are put forward. Lyapunov exponent is calculated to judge whether there is chaos in CNN, and the influence on chaos characteristic caused by parameters of CNN model is discussed, then channel assignment algorithm based on CNN is proposed. Simulation results indicate that CNN has stronger ability to search global optimal solution and quicker convergence speed than Hopfield network, for its complicated transient chaos characteristic.
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