ma1104

北航刘金锟老师的《智能控制》附带的完整matlab源程序！(Source codes （matlab）for the book "Intelligent Control" by Jinkun LIU in Beihang University!)

说明：  BAM是一种两层的异联想，内容可寻址存储器组成的反馈网络。 分类：离散，连续 和自适应BAM等。 1987年和1988年由Kosko提出的BAM型。 网络运行是双向的。对网络的一端输入信号，则可在另一端得到输出，该输出又反馈回来，经过多次反复，直到网络达到稳态为止(BAM is a two-tier Heteroassociation, content addressable memory component of the feedback network. Classification : discrete, continuous and adaptive BAM other. In 1987 and 1988 by the BAM Kosko type. The operation of the network is a two-way. The network side input signal can be received at the other end output, the output feedback to come back again, repeatedly, until the network reached so far Steady)

priodgram matlab code

这是一篇lingo的教程。LINGO 是用来求解线性和非线性优化问题的简易工具。LINGO 内置了一种建立最优化模 型的语言，可以简便地表达大规模问题，利用 LINGO 高效的求解器可快速求解并分析结果。(LINGO is a simple tool for solving linear and nonlinear optimization problems. The built-in LINGO to establish an optimization model of language, large-scale problems can be easily expressed, using the LINGO solver efficiency and results can be quickly solved. )

This program generate pitch estimation fro signal.

单神经元PID控制器的仿真与应用实例。比较常规PID控制器，得其优缺点(single neuron PID controller simulation and application examples. Comparing Conventional PID controller, to gain advantages)

matlab实现的k均值聚类算法，可以实现对大量数据的有效分类(matlab implementation of the k-means clustering algorithm, can achieve a large amount of data on an effective classification)

说明：  关于电力系统状态估计快速分解算法的MATLAB程序(Power system state estimation algorithm for the rapid decomposition)

说明：  1对一段音频进行matlab双声道限时取样，并画图 2产生一段随机整数噪声，并加入到原样本中(1 on a two-channel audio matlab limited sampling, and drawing a random integer generated noise 2, and added to the original sample)

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.)