K目标跟踪中的K均值聚类法 KMeans

通信原理实验生成软件及相关代码，调制解调（C生成）(Communication principle experiment generation software and related codes, modulation and demodulation (C generated))

实现了PID控制与自适应模糊PID控制的比较 亲测simulink仿真结果 (Adaptive fuzzy PID control)

一种新的mUSIC方法，非常好用( spatial smoothing MUSIC, very good!)

汽车动力学中汽车四分之一和二分之一MATLAB模型，还有路面谱模型，可以直接运行，效果良好(Vehicle dynamics in a quarter and half car MATLAB model, as well as road spectrum model, you can run directly to good effect)

求序列的自相关和互相关值的matlab实现！(The function for solving the autocorrelation and cross correlation values)

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. )

matlab编程与工程应用第二版课后习题答案(Matlab programming and engineering application second edition exercises answer after class)

三个简单地使用matlab实现的遗传算法的程序，为初学者提供一个入门知识(Three simple genetic algorithm matlab implementation of the program, to provide the knowledge of an entry for beginners)

对GPRmax的数据进行成图的一些matlab程序(Some data on GPRmax programs into graphs)

一篇有关各类型小波应用于图像增强的算法论文，质量较高，适合初学者阅读 (failed to translate)