helloworld.tar

802.16 physical layer simulation through diferent SUI Channel.

matlab的应用教程，ppt格式，教学用(the application of matlab tutorials, ppt format, teaching)

说明：  图像处理之Poisson图像融合（含程序，图片）(image fusion of Poisson)

产生M序列，可以作为系统的输入，经过系统辨识后得到输出，进而得到系统的传递函数(M sequences generated can be used as the input, output obtained through system identification, and further to the transfer function)

分类器，用于识别数字，可以做到二分类，比如，分辨0和1。(Classifier for identifying numbers, you can do two classification, for example, distinguish between 0 and 1.)

本文的秘密编码离理想的码率还很远，建立的无 条件秘密通信系统的稳定性和秘密性有待进一步证明，无条件安全系统秘密编码 方案还处于起步研究阶段，还有很多新的突破点等待研究。(Stability and secrecy of the secret coding bit rate still far from the ideal, the establishment of the unconditional secret communication system needs to be further proof, the the unconditional security system secret coding scheme is still at an early research stage, there are a lot of new breakthrough wait for research .)

MATLAB Binary Frequency Shift Keying

快速独立元分析,matlab程序 (fast ICA)

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...)

随记减量法是从结构的随机振动响应信号中提取该结构自由衰减振动信号的一种方法-With the mind Reduction Act(Reduction Act is credited with random vibration response of the structure from the signal to extract the structure of a method-With free decay vibration signals the mind Reduction Act)