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CMA-ES
- The optimization behavior of the self-adaptation (SA) evolution strategy (ES) with intermediate multirecombination (the (=I )-SA-ES) using isotropic mutations is investigated on the general elliptic objective function. An asymptotically e
The-Multi-user-Detection-ALGORITHM
- 联合智能(JI-MUD)多用户检测算法是由粒子群优化(PSO)算法,遗传算法(GA)和模拟退火(SA)算法-the joint intelligent multi-user detection (JI-MUD) algorithm which was composed by particle swarm optimization (PSO) algorithm, genetic algorithm (GA) and simulated annealing (SA) algorithm was p
SA-TSP
- 使用模拟退火算法来解决TSP旅行商优化问题-Using simulated annealing algorithm to solve TSP traveling salesman optimization problem
PSO(粒子群)-SA（模拟退火）
- 粒子群算法-模拟退火算法,关于matlab的算法说明(Particle swarm optimization-simulated annealing algorithm)
神经网络入门13课源码
- 神经网络入门13课源码 第一课 MATLAB入门基础 第二课 MATLAB进阶与提高 第三课 BP神经网络 第四课 RBF、GRNN和PNN神经网络 第五课 竞争神经网络与SOM神经网络 第六课 支持向量机( Support Vector Machine, SVM ) 第七课 极限学习机( Extreme Learning Machine, ELM ) 第八课 决策树与随机森林 第九课 遗传算法( Genetic Algorithm, GA ) 第十课 粒子群优化( Part