mv

weight trajectories for two different initial conditions an step-size( variance of u, denoted by var_u, can be changed. Also, the values of the step-size, in the variable mu, and the value of the initial weight estimate, in the variable w_init, can be changed.)

基于matlab的电压源型整流器的仿真，可以通过最后的波形得出结论(Type of voltage source rectifier based on matlab simulation, can pass the final waveform concluded )

主要是用于图像能量的提取，效果不错，可以使用(Is mainly used to image the extraction of energy, the effect is good, can use)

here we will estimate delay time added to the channel and we will plot the error

说明：  字典树的基本功能是用来查询某个单词（前缀）在所有单词中出现次数的一种数据结构，它的插入和查询复杂度都为O(len),Len为单词（前缀）长度，但是它的空间复杂度却非常高，如果字符集是26个字母，那每个节点的度就有26个，典型的以空间换时间结构。(The basic function of the dictionary tree data structure is used to query a number of times a word (prefix) appears in all the words, which insertion and query complexity are O (len), Len is a word (prefix) length, but its space complexity is very high, if the character set is 26 letters, and that the degree of each node will have 26, the typical structure of space for time.)

摘要：应用Matlab/Simulink对实验室研制的六自由度运动平台位置反解建模、仿真、分析，通过对上平台进行垂 荡、纵荡、横荡、纵摇、横摇和艏摇六个自由度方向上的运动仿真分析，得到了六个液压缸的长度变化规律，更直观的 了解了平台在不同运动情况下的运动规律 (Abstract: The six degrees of freedom motion platform location, Matlab/Simulink laboratory developed anti-solution modeling, simulation, analysis, on a platform heave, vertical swing, sway, pitch, roll and yawing sixdegrees of freedom on the direction of motion simulation, six hydraulic cylinders of length variation, a more intuitive understanding of the law of motion of the platform in the case of different sports)

最小均方自适应滤波器，两个基本过程：滤波和自适应(LMS adaptive filter, two basic processes : adaptive filtering and)

拉格朗日插值代码，非常简洁的代码，适合学生作业及学习，(On Lagrange Interpolation code, the very concise of the code, suitable for students job and learning,)

codage matlab winmax mimo

说明：  多种方式求解TSP问题，有遗传算法，A*算法，D算法，模拟退火，神经网络等(A variety of ways to solve TSP problem, a genetic algorithm, A* algorithm, D algorithm, simulated annealing, neural networks)