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MIMO是移动4G的通信技术，但是受到地形和外部建筑的影响，收到的无线信号含有多径，产生严重的码间干扰，文章中阐述了用MMSE方法对信号进行均衡，很好得恢复MIMO信号(4G MIMO mobile communication technology, but by the terrain and outside the building, the wireless signal containing the received multipath produce serious inter-symbol interference, the article describes a method of using the MMSE equalization of the signal, the recovery was very good MIMO signal)

with this code tou can get 2dimonsional fft of image

收集的matlab符号运算的电子书籍与文档资料，对于熟悉了matlab数值运算想对符号计算有所了解的可以看看。(Matlab symbolic operation collected the e-books and documentation, for those familiar with the matlab numerical computation would like to understand the symbolic computation can take a look at.)

QAM调制下的物理层网络编码调制与解调方案仿真程序(Physical layer network coding modulation and demodulation simulation program QAM modulation scheme under)

魔术轮胎模型在simulink中的应用。。。。。。。。。。。。(Simulink model of magic tire in MATLAB)

说明：  利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域(Using computer simulation operations, the problem-solving process is transformed into a process similar to the crossover and mutation of chromosomal genes in biological evolution. When solving more complex combinatorial optimization problems, compared with some conventional optimization algorithms, better optimization results can usually be obtained faster. Genetic algorithm has been widely used in the fields of combinatorial optimization, machine learning, signal processing, adaptive control and artificial life)

说明：   数据挖掘的重要算法SVM的实现,用matlab(important data mining algorithms to achieve SVM using Matlab)

说明：  复杂网络经典BA模型以及两个改进的BA模型，分别封装成函数。输入参数有：网络节点个数，初始节点个数，新店与就网络连边的数目，初始网络边的连接(Complex network classic BA model and two improved BA model, are encapsulated into a function. Input parameters: the number of network nodes, the initial number of nodes, the new store on the edge of the network even number side of the initial network connection)

函数逼近教学例子,可以选择不同训练算法。(Function approximation teaching example, you can choose different training algorithms.)

对线性均衡、判决反馈均衡和最大似然序列估计均衡等三种方法的实现和误码率的分析。(Of linear balanced, decision feedback equalizer and maximum likelihood sequence estimation of three methods such as balanced realization and BER analysis.)