FastICA_testing_wav_img_samples

transmission reception optical fiber

说明：  his file contains a summary of what you will find in each of the files that make up your CC application.

使用LMI方法解决一个带约束的滚动时域优化问题(Constrained Receding Horizon Control Demonstration of Receding Horizon Control (RHC) using LMI)

这是我多年MATLAB编程的技巧汇总，希望对大家有用。里面包含命名规则，怎样优化程序等等。(This is my years of MATLAB programming skills summary, I hope useful for everyone. Which contains the naming rules, how to optimize procedures.)

用训练数据优化DPCM方法，对一个余弦信号数据进行标量量化。(we take optimize the training data DPCM method for the cosine signal data scalar quantization to get a wonderfull understanding.)

farrow滤波器测试实例，包括线性和多项式farrow结构比较，幅度相位比较，以及分数延迟可变的farrow结构(farrow filter testing procedures, structures and linear polynomial farrow farrow structure comparison, fractional delay variable farrow structure instance.)

基于肤色的人脸检测MATLAB源代码皮肤检测的最终目标是构建一个决策规则，并以此将图像中的像素划分为肤色和非肤色两类，一般通过引入一个衡量像素点颜色与“标准肤色”的距离而实现的，该距离是由相应肤色建模的方法决定的(Face detection based on skin color skin detection MATLAB source code for the ultimate goal is to build a decision-making rules, and use of the image pixels into skin and non skin types, usually by introducing a measure of the pixel color with the " standard colors" achieved the distance, the distance of the corresponding color from the decision modeling approach)

基于matlab模糊pid的仿真，主要应用于工业控制方面。(fiizzy pid control)

虽然奇异值分解（SVD）和特征值分解（EVD的）是行之有效的，可以通过先进的设施设备先进的算法，它不是通常所说，有一个内在的迹象，可以显着影响的不确定性的结论计算及诠释来自其结果。我们提供一个解决方案，标志模糊的问题确定了从奇异向量的内积和个人数据载体签署奇异向量的迹象。该数据可能有不同的载体，但它有它自身的定位和实际意义的选择方向，其中多数的向量点。这可以通过评估发现了内心的签署标志产品的总和。(Although the Singular Value Decomposition (SVD) and eigenvalue decomposition (EVD) are well-established and can be computed via state-of-the-art algorithms, it is not commonly mentioned that there is an intrinsic sign indeterminacy that can significantly impact the conclusions and interpretations drawn from their results. We provide a solution to the sign ambiguity problem by determining the sign of the singular vector from the sign of the inner product of the singular vector and the individual data vectors. The data vectors may have different orientation but it makes intuitive as well as practical sense to choose the direction in which the majority of the vectors point. This can be found by assessing the sign of the sum of the signed inner products. )

Watermarking algorithms built using matlab