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MATLAB Simulations for Radar Systems DesignMATLAB_Codecirc_array.rar(MATLAB Simulations for Radar Systems Design MATLAB_Code circ_array.rar)

该算法为最小均方误差滤波，对输入信号进行滤波，输出滤波后的波形和误差(The least squares algorithm, the input signal is filtered, and the filtered output waveform error)

DAB型全桥DC-DC变换器与3相PWM型变换器级联仿真，可用于充放电系统及新能源领域，实现能量的双向流动。(DAB full-bridge DC-DC converter with three-phase PWM converter cascade simulation model can be used to charge and discharge systems and new energy field, two-way flow of energy.)

MIMO系统接收天线数不同时的信道容量对比(In contrast to MIMO system capacity of receiving antenna book is not the same channel)

一些MATLAB教学程序,对初学者很有帮助(some MATLAB teaching procedures, helpful for beginners)

matlab code for solving 8Queens by GA algorithm

这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下，自行完善了在一定先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。 全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。 调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。 调用最小风险贝叶斯分类器决策子函数时，根据先验概率，再根据自行给出的5*5的决策表，通过比较概率大小判断一个体重身高二维向量代表的人是男是女，放入决策数组中。 主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小风险贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到在一定先验概率条件下，决策表中不同决策的错误率的统计。 (This is a pattern recognition classifier minimum risk Bayes design .In reference to the case of routine , self- improvement in a certain a priori probability conditions, male , female and total error rate error rate statistics , into which each array . All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions . Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector The third step is the application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function . Bayesian classifier )

说明：  在DOS下一个VGAL库的源程序。用TC3进行编译成功。(DOS VGAL a library of the source. Compiled with TC3 success.)

提出了一种求解电磁场有限元 边界元混合法所生成的线性方程组的有效方法 ———内观 法结合多波前法.由于该线性方程组的系数是一个部分稀疏部分满填充的矩阵,为了加速求解,应用内观法将系数矩阵分为 2块,一块是有限元法形成的稀疏矩阵,另一块是边界元法生成的满阵,然后用多波前法求解稀疏矩阵方程,用高斯 约当消去法解满阵方程. 采用该方法,计算了二维多层介质柱体的雷达散射截面.计算结果表明,该方法的计算效率远远高于传统的高斯法.(Proposed for solving mixed finite element boundary element linear equations generated by an effective method of Vipassana--- a combination of multi wave front method. Since the coefficients of linear equations is a part of the sparsely populated part of the full matrix, in order to speed up the solution, application of Vipassana coefficient matrix is ​ ​ divided into two, one is the finite element method for the formation of the sparse matrix, the other is the boundary element method generates the full array, and then use the multifrontal method for solving sparse matrix equation Gauss Jordan elimination method with full matrix equation solution. use this method to calculate the two-dimensional multi-layer dielectric cylinder of the radar cross section. The results show the computational efficiency of this method is much higher than the traditional Gaussian law.)

说明：  神经元整合发放模型。输入刺激参数可以获得一段时间内的动作电位(integrate and fire model.)