snake

书名：[MATLAB语言常用算法程序集].(龚纯).清晰版 内容：插值，函数逼近，特征值计算，数值微分，数值积分，方程求根，非线性方程组求解，线性方程组的直接法，线性方程组的的迭代法，随机数生成，特殊函数计算，常微分方程的初值问题，偏微分方程的数值解法，数据统计和分析。(Title: [MATLAB algorithms commonly used in assembly language]. (Gong pure). Clearer view of the contents: interpolation, function approximation, eigenvalue calculation, numerical differentiation, numerical integration, finding roots of equations, nonlinear equations, linear equations group, direct, linear equations of the iterative method, random number generation, calculation of special functions, initial value problems for ordinary differential equations, numerical solution of partial differential equations, statistics and analysis.)

在matlab环境下对ofdm进行仿真的程序(In matlab ofdm simulation under the environment of the procedure)

基于matlab的直序扩频通信系统仿真模型(Matlab-based direct-sequence spread spectrum communication system simulation model)

求解无约束优化问题的算法效率与性能的测试函数(Solving the unconstrained optimization problem, the algorithm efficiency and performance of test functions)

实现数字二阶锁相环仿真模拟，基于matlab(Simulation of digital two phase phase locked loop on matlab)

MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。(MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)

对锅炉现场数据辨识后，分别采用GPC和DMC进行控制，采用m文件进行编程。(The boiler field data identification, respectively GPC and DMC control, use the m file programming.)

一份经典的支持向量机基本原理的课件，找了好久，希望对大家有帮助。(A classic basic principle of SVM courseware, looking for a long time, we want to help.)

neural network coding for image classification

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