Wiener_standalone.tar

滤波器设计，对一给定随机信号进行滤波。一个较为完整的示例，包含信号的产生与分析过程(Filter design, for a given random signal filtering. A more complete example, including the process of signal generation and analysis)

WAVELET demonstration

AT91SRAM7 configuration file is very good very practical hope to help you. Learn each other and work together. Take out a Shared

matlab中关于dsp的全部程序 还有仿真模块 (matlab )

matlab中的symerr函数可以求得误码率 只要看下文件中最后那个例子，这个函数你就会用了(matlab in symerr function as long as the error rate can be obtained see next document in this last example, this function you will use the)

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. )

说明：  本程序有传统的MUSIC算法和基于分数低阶矩的MUSIC算法 在alpha稳定分布下的性能仿真(this programme contain the performence of traditonal MUSIC algorithm and FLOC MUSIC algorithm under the alhpa steady distrubution)

混沌系统van_der_pol控制器的仿真程序,可以通过此程序仿真van_der_pol控制器的混沌系统及仿照此程序仿真其它混沌系统。(The synchronization of chaos system by van_der_pol control.)

calc md machin trualaz zzzzeaze

matlab adaptive filter project codes