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GA
说明： 遗传算法MALAB程序包，包括适应度、计算、选择交叉、变异等子程序(GA MALAB package, including fitness, calculation, select crossover and mutation subroutine)
- 2013-10-15 17:19:39下载
- 积分：1
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MIMO_OFDM
mimoofdm仿真，主要是不同信道估计的对比，可以运行(mimoofdm simulation, mainly comparing different channel estimation can run)
- 2021-02-19 17:49:44下载
- 积分：1
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Spectral-Correlation-of-Modulated
Spectral Correlation of Modulated
- 2014-02-20 10:48:18下载
- 积分：1
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digitalband-passfilter
用脉冲响应不变法和双线性变换法设计数字带通滤波器(Impulse response using the same method and bilinear transformation method the number of band-pass filter design)
- 2009-06-05 18:26:36下载
- 积分：1
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myGPC
说明： GPC代码 实现广义预测控制 可以设置预测时域和控制时域(GPC GPC code can set the prediction horizon and control the time-domain)
- 2011-03-30 21:02:08下载
- 积分：1
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knn_map
用得最多的是最近邻，此处上传的是K-近邻，即k＝1。matlab环境下的代码。附有实例。(used most often is the nearest neighbor, here is uploaded K-neighbor, k = 1. Matlab environment code. With examples.)
- 2007-04-11 17:05:09下载
- 积分：1
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apsk-ruanpanjue-
apsk软判决算法的仿真，根据星座特点进行算法的简化，减低复杂度(Simulation apsk soft decision algorithm based on the characteristics of the constellation simplified algorithm to reduce the complexity of)
- 2013-12-05 18:02:41下载
- 积分：1
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遗传算法GA
matlab 遗传算法GA，粒子群算法PSO,蚁群算法AS 前段时间上智能计算方法实验课上，自己做的程序。帖到这里，希望有人能改进它们，交流经验这样更有价值。 遗传算法解决最小生成树问题，PURFER编码。 粒子群算法做无约束最优化问题。 蚁群算法解决TSP问题。 (matlab genetic algorithm GA, particle swarm optimization PSO, some time ago on the ant colony algorithm intelligent calculation AS experimental course, make their own programs. Posts here, I hope someone can improve their exchange of experience is more valuable. Genetic algorithm to solve minimum spanning tree problem, PURFER code. Particle Swarm do unconstrained optimization problems. Ant colony algorithm to solve TSP problem.)
- 2015-06-28 11:47:54下载
- 积分：1
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EFG1D
一维meshfree 的EFG算法！！属于T. Belytschko这种大师人物的经典例程(One-dimensional meshfree algorithm of EFG! ! T. Belytschko are such masters of the classic characters routines)
- 2007-08-15 11:15:30下载
- 积分：1
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fig7_34
We see that HTH matrix is almost diagonal as the off diagonal elements are nearly zero. So we are getting exact estimation in case of PRN INPUT due to diagonality of HTH matrix. As seen that the unknown inpulse response ( h ) and estimated impulse response ( hth ) are coming out to be exactly same. The estimation even gets better for large N .as we get the HTH matrix perfect diagonal. So we come to know that we can estimate the unknown parameters exactly when PRN input is used.
- 2013-05-02 02:56:07下载
- 积分：1
