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说明：  比较全面的ICA算法Matlab程序，可以作为ICA研究的基础(More comprehensive Matlab procedures ICA algorithm can be used as the basis of the study ICA)

authorware小例子 1、打台球 2、古诗欣赏 3、投篮 4、移动图形 5、制作一个钟表(authorware small example 1, billiards 2, 3 poetry appreciation, shooting four, five mobile graphics to produce a watch)

图像的自适应魏纳滤波 MATLAB的，(Image Adaptive Filter WEI Na MATLAB, every word uttered)

时频分析工具箱中提供了计算各种线性时频表示和双线性时频分布的函数(Time-frequency analysis toolkit provides the calculation of linear time-frequency representation and bilinear time-frequency distribution function)

用MATLAB来仿真FSK、PSK、DPSK的调制、解调过程，并通过实验来比较它们的误码率和信噪比的关系。内附有matlab源代码(Using MATLAB to simulate FSK, PSK, DPSK modulation, the demodulation process, and to compare their bit error rate and signal to noise ratio by the empirical relationship. Enclosed is the matlab source code)

Optical Fiber Telecommunications Volume VI-A， a new book which precents Optical Fiber Telecommunications component to system

针对滚动轴承故障信号具有非平稳、非高斯的特点，提出了将时域分析与小波分析相结合的方法对滚动轴承进行故障诊断。在研究不同信号分析方法理论的基础上，以滚动轴承外圈故障振动信号为例，采用多种信号处理方法进行了分析。结果表明，各种分析方法在分析轴承故障时的特点各不相同，在实际使用中，可将时域分析与小波分析综合使用，实现轴承状态的实时监测与故障的准确定位。(For rolling bearing fault signals have non-stationary, non-Gaussian, we proposed the time-domain analysis and wavelet analysis method of combining the rolling element bearing fault diagnosis. In the study of different analytical methods based on the theory of signal to the outer ring rolling bearing fault vibration signal, for example, using a variety of signal processing methods are analyzed. The results show that a variety of analytical methods in the analysis of the characteristics of bearing failure vary, in actual use, can be time-domain analysis and synthesis using wavelet analysis, to achieve accurate positioning of the bearing condition monitoring and real-time fault.)

RLS算法和LMS算法在系统识别中的应用(RLS algorithm and the LMS algorithm in system identification application )

几种先进PID控制算法的matlab仿真源代码。(Several advanced PID control algorithm matlab simulation source code.)

说明：  这个是用基本粒子群优化算法解两个测试函数的最小值问题。(This is a fundamental particle swarm optimization algorithm using two test function solution of the minimum problem.)