case14

跳频扩频通信系统的主要仿真程序，包括扩频，测试和演示(The main frequency hopping spread spectrum communication system simulation program, including spread spectrum, testing and demonstration)

本代码是描述串联机器人的雅克比矩阵的推导和灵巧度的分析(this code is to describe the Jacob matrix of the serial robot and its dexterity)

说明：  matlab matlab v matlab matlab

基于MATLAB的平面度评定方法，介绍了计算方法(Based on MATLAB flatness evaluation method, calculation method introduced)

自己写的haffman编码源代码，用matlab实现的，欢迎指正。(himself wrote the source code haffman coding using Matlab to achieve, and welcome correction.)

对信号进行常数模算法的仿真。这类算法对信号具有很好的均衡效果，且运算简单。(Constant modulus algorithm for the simulation of the signal. Such algorithms on the signal has a well-balanced effect, and simple operation.)

在核空间中进行pca，简称kpca的源码(kernel principle component analysis )

说明：  时间序列经典设计程序，适合初学者学习使用！(Time Series classic design program, for beginners to learn to use!)

独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S+ N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...)

用matab实现离散信号a(n)和b(n)的线性卷积和圆周时域卷积，并显示。(A discrete signal with matab a (n) and b (n) linear time-domain convolution and circular convolution, and display.)