newmark827

说明：  用于实现常规AM调制的MATLAB源程序。(Matlab demonstration script for AM modulation. The message signal is+1 for 0 < t < t0/3,-2 for t0/3 < t < 2t0/3 and zero otherwise.)

在matlab与SystemGenerator的平台下实现零阶时延数字正切锁相环。此模块最终能达到与输入信号同频率。(In the matlab, and SystemGenerator the platform, zero-order delay tangent digital phase-locked loop. This module is ultimately to reach input signal with the same frequency.)

mpa算法,可以实现四个资源块 ，六个用户之间的迭代用于非正交多址接入(Multi-user detection algorithm for MPA)

genetic algorithm program for power system

high voltage converter

用matlab编的计算传感器配置的有效独立法、模态置信因子的一些小程序(EI MAC)

Abstract The study of digital signal processing normally concentrates on the design, realization, and application of single-input, single-output digital filters. There are applications, as in the case of spectrum analyzer, where it is desired to separate a signal into a set of sub-band signals occupying, usually nonoverlapping, portions of the original frequency band. In other applications, it may be desired to combine many such sub-band

分数阶傅里叶变换的二维峰值搜索，针对线性调频信号的峰值能进行很好估计(D peak search Fractional Fourier transform for the peak chirp signal can be well estimated)

信号包络，提出信号包络，便于观察信号波动过程，非常有用(Signal envelope, put forward the signal envelope, easy to observe the process of signal fluctuations, very useful)

费希尔线性判别分析代码 Find the Fisher linear separator w (a column vector). X is is the training set (X is a matrix. Each row of X is a vector containing the features of a single sample). y is a column vector with the labels of the training set (1 and -1). alg is a number between 1 and 3 that specifies how to find w: alg = 1: w is the generalized eigenvalue of A,B. alg = 2: w is the solution to Bw = (mu_1-mu_2) alg = 3: solve the corresponding regression problem( Find the Fisher linear separator w (a column vector). X is is the training set (X is a matrix. Each row of X is a vector containing the features of a single sample). y is a column vector with the labels of the training set (1 and-1). alg is a number between 1 and 3 that specifies how to find w: alg = 1: w is the generalized eigenvalue of A,B. alg = 2: w is the solution to Bw = (mu_1-mu_2) alg = 3: solve the corresponding regression problem)