3Devaluationcode

LMS algorithm PIL cosimulation for DM642 EVM.

matlab函数库大全，首字母索引，帮助您快速找到您所需要的函数~(matlab library Guinness, the first letter of the index to help you quickly find the function you need ~)

压缩感知matlab代码，在欠采样的条件下实现模数转换。在超宽带和频谱混叠的情况下亦可通过本软件仿真。具有较高的参考价值。(Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral support. A more challenging problem is spectrum-blind sub-Nyquist sampling of multiband signals. For example, cognitive radio receivers face with this kind of problem whenever sensing the RF spectrum at their surroundings. The modulated wideband converter (MWC) is the first system for sub-Nyquist sampling, which can be realized with existing devices and handle wideband analog signals.)

根据PSO算法原理，在MATLAB中编程实现基于PSO算法的函数极值寻优算法，程序前面给出了PSO算法参数设置，种群初始化，寻找初始极值，迭代寻优，最后通过算法反复迭代300次，画出每代最优个体适应度值变化曲线，最后通过对比发现说明PSO算法具有较强的函数极值寻有能力，谢谢，希望对大家有帮助。 (According to the principle of PSO algorithm in MATLAB programming function PSO algorithm based on extreme value optimization algorithm, the preceding program gives the PSO algorithm parameter settings, population initialization, looking for initial extreme value, iterative optimization, and finally through the iterative algorithm 300 times draw the best individual fitness value of each generation curve, and finally by comparing the findings indicate that PSO algorithm has strong function extreme ability to find, thank you, we want to help.)

这是一个潮流计算的程序。运用了牛顿—拉夫逊法。求出了各节点电压，功率分布。(This is a process flow calculation. The use of the Newton- Raphson method. Obtained each node voltage, power distribution.)

粒子群算法matlab代码 (PSO matlab code )

比较了三种学习方法 1 gradient descent 2 steepest descent with line search 3 conjugate gradient method. 三种方法都在一个.m文件中被实现。(compare three learning methods: 1 gradient descent 2 steepest descent with line search 3 conjugate gradient method.)

Simulation Of Patch Antenna Using MATLAB

4Cyclist problem simulation model Four cyclists are at the desert. Each of them starts from a different location and tries to reach the other ones. Cyclist 1 goes straight to cyclist 2, cyclist 2 straight towards cyclist 3 etc. such that finally the cyclist 4 goes straight towards cyclist 1. Form the equations, build a Simulink-model and find out the meeting point of the cyclists by simulating the system with the following initial values:

Artifical neural network forecasting. The code helps so much in training and testing data. It also developed in order to predict another new data base on the observed data