matlabtest10

necessary pdf for wimax

这是数学专业的数学建模的课程设计，很有用啊，希望大家踊跃下载啊(This is the mathematical modeling mathematics curriculum design, very useful, ah, ah hope you actively download)

说明：  一维信号BP重构算法，先生成稀疏度为K的稀疏矩阵，再加入高斯白噪声进行算法重构以及质量衡量。(BP signal reconstruction algorithm for one dimensional, Mr. into sparse matrix sparsity of K, then the Gauss white noise and measure the quality of reconstruction algorithm.)

说明：  最速下降法是迭代法的一种,可以用于求解最小二乘问题(线性和非线性都可以)。在求解机器学习算法的模型参数，即无约束优化问题时，梯度下降（Gradient Descent）是最常采用的方法之一，另一种常用的方法是最小二乘法。在求解损失函数的最小值时，可以通过梯度下降法来一步步的迭代求解，得到最小化的损失函数和模型参数值。反过来，如果我们需要求解损失函数的最大值，这时就需要用梯度上升法来迭代了。在机器学习中，基于基本的梯度下降法发展了两种梯度下降方法，分别为随机梯度下降法和批量梯度下降法。(The steepest descent method is a kind of iterative method, which can be used to solve the least squares problem (both linear and nonlinear). In solving the model parameters of machine learning algorithm, that is, unconstrained optimization, gradient descent is one of the most commonly used methods, and the other is the least square method. When solving the minimum value of loss function, the gradient descent method can be used step by step to get the minimum value of loss function and model parameters. Conversely, if we need to solve the maximum value of the loss function, then we need to use the gradient rise method to iterate. In machine learning, two kinds of ladders are developed based on the basic gradient descent method)

一些直扩和跳频的程序，还有CDMA的程序(DSS、FH、CDMA)

地板砖铺设，从800*800,400*400,600*300和300*300中选择，进行最优铺设。(put dibanzhuang)

实现彩色图象的读取,以及回度图象的读取,及相关的变换(Achieve color image reading, and reading back of the picture, and the associated transformation)

一篇关于Matlab的很好的教程，对于学习matlab来讲是一个不错的选择(A good tutorial on Matlab, matlab for learning is a good choice in terms of)

用matlab实现了SVM算法，并且对两类点进行了分类，给出了图形化的结果。(SVM algorithm is implemented using matlab, and two points on the classification, given the graphical result.)

qpsk调制解调，外加取样判决脉冲成型，可以加入任何程序模块中，保证解码译码的便利性(qpsk modem, plus a sample sentence pulse shaping, you can add any program module to ensure ease of decoding decoding)