Signals-Systems-and-Transforms-4E-by-charles-l

Tasks of the machine learning lessons

利用最速下降法计算最小曲面的面积，初始条件为0，边界条件为正方形固定边界。(Using steepest descent method to calculate the minimum surface area. Initial condition is 0, while boundary condition is square fixed values.)

共振解调法轴承诊断 包络谱包括外环内环滚子故障诊断(Resonance demodulation method envelope bearing diagnostic spectrum, including outer inner roller Troubleshooting)

MATLAB中一些经典的算法汇总。聚类算法、概率算法、神经网络、模拟退火等算法(Some classic algorithms in MATLAB are aggregated. Clustering algorithm, probabilistic algorithm, neural network, simulated annealing algorithm and so on.)

It is a gui used to zoom a picture or u shrink it. It is very interesting! I hope u will like it!

LDPC码的完整的编译码，用MATLAB编写的遗传算法路径规划，解耦，恢复原信号。( Complete codec LDPC code, Genetic algorithms using MATLAB path planning, Decoupling, restore the original signal.)

蚁群算法ACO的应用，包括图像匹配，边缘检测，点检测，以及遗传算法GA(ACO ACO algorithm applications, including image matching, edge detection, detection, and genetic algorithm GA)

说明：  常微分方程的MATLAB解法教程详解，包含ODE45等经典函数的例子(Detailed tutorials in how to get Solution of Ordinary Differential Equations by MATLAB , includingclassic example of a function ODE45,ode23,etc)

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )

背景差分建模运动目标检测和跟踪，附有一个实验视频，点开就跑(Background subtraction modeling moving object detection and tracking, with an experimental video, opening and ran.)