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遗传算法优化RBF径向基神经网络的matlab程序源代码。(Genetic Algorithm RBF radial basis function neural network matlab source code.)

Quadratic interpolation search method M-file

Matlab2012b2010bmatlab7的下载地址安比较及常见问题 (Download Ann Matlab2012b2010bmatlab7 comparison and FAQs)

如何使用MATLAB编程，里面有详细的说明，大家可以试试。满好的教程(How to use the MATLAB programming, which is described in detail, we can try. Man good tutorial)

介绍了 Cohen类双线性时频分布并针对交叉干扰项影响无法完全消除的问题进行了重排时频变换以提取及分辨 含有白噪声和窄带周期干扰的局部放电信号。处理仿真和现场检测到的局部放电超声信号时根据白噪声和窄带 周期干扰信号在时域上的平稳性特性发现重排 Cohen类时频变换方法不仅可以很好地将局放信号和背景噪声以 及窄带周期干扰信号分辨开来,而且大大减弱并抑制了交叉干扰项的影响,保持了更高的时频分辨率和时频聚集 性,从而验证了重排 Cohen类时频变换方法的有效性。 (In order to express the partial discharge ( PD) information of gas insulated switchgear ( GIS) in time-frequency domain, weintroduced theCohen? s class bilinear time-frequency distribution and its reassigned time-frequency transform method to pick up and distinguish theultrasonic signals in field from the whitenoises and narrow band periodic interference signals using the acousticemission ( AE) technology. After the processing of the simulated and PD ultrasonic signals in field, and according to the stationary feature of white noises and narrow band interference signals, wedraw a conclusion that the reassigned time-frequency distribution method can not only distinguish thePD signal from back ground noises and narrow band interference signals, but also decrease and restrain the influenceof cross-items, and acquire better time )

说明：  利用SLM和PTS降低OFDM系统PAPR，并得到相应的对比图形(Using SLM and PTS techniques to reduce the PAPR of OFDM system,and figure the CCDF)

基于分数阶自抗扰控制的车辆1/4模型在混合路面启动工况仿真(Fractional-based vehicle ADRC 1/4 model start in the mixed road conditions simulation)

Project thesis with included matlab codes of ICI Cancellation in OFDM systems.

摄影测量中的前交后交方法计算出实地三维坐标(Photogrammetry and submit it before the delivery method to calculate three-dimensional coordinates of the field)

In this project an adaptive beamforming technique is proposed based on directly minimizing the BER1. A particular approach that has shown real promise in achieving substantial capacity enhancements is the use of adaptive antenna arrays. A beamformer appropriately combines the signals received by the different elements of an antenna array to form a single output. Classically, this has been achieved by minimizing the mean square error (MSE) between the desired output and the actual array output. It is demonstrated that minimum BER (MBER) approach utilizes the antenna array elements more intelligently than the standard MMSE2 approach, since it directly optimizes the system’s BER performance rather than minimizing the MSE, where the latter strategy often turns out to be deficient.