View_UsingViewsTest

说明：  里面什么都有大家可以自己查看，里面说的都很详细，可以借鉴一下，请注明版权。(Has everything you can own view, which says very detailed, you can learn about, please indicate the copyright.)

说明：  在OFDM系统中，采用限幅法降低峰均功率比，该文件包括了流程图和matlab源码(In OFDM system, using limiting PAPR reduction method, the document includes flow charts and source code matlab)

说明：  bp神经网络，实现bp神经网络的分类，用matlab语言编写(bp neural network, the realization of bp neural network classification, using matlab language)

Cuckoo search (CS) is an optimization algorithm developed by Xin-she Yang and Suash Deb in 2009.[1][2] It was inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds (of other species). Some host birds can engage direct conflict with the intruding cuckoos. For example, if a host bird discovers the eggs are not their own, it will either throw these alien eggs away or simply abandon its nest and build a new nest elsewhere. Some cuckoo species such as the New World brood-parasitic Tapera have evolved in such a way that female parasitic cuckoos are often very specialized in the mimicry in colors and pattern of the eggs of a few chosen host species [3]

描述了13阶巴克码信号的特性，画出了图形，并做了脉冲压缩处理，比较了用一般旁瓣抑制滤波器与等副瓣法设计旁瓣抑制滤波器进行旁瓣抑制的差别，给出了图示。(Describe the 13 order Barker code signal characteristics, draw the graphics, and the pulse compression processing, compared with the general sidelobe suppression filter with side flap design of sidelobe suppression filter for sidelobe suppression of difference, gives some graphic.)

多输入多输出系统，应用最小均方差均衡器的误码率性能曲线(Multi-input multi-output system, the application of the minimum mean square error equalizer BER performance curve)

一个关于无向图推理模型的代码，可用于图像处理(An undirected graph inference on the model code)

Maximum A Posteriori probablity (MAP) algorithm

能够实现经典谱估计和现代谱估计的方法的比较，而且表现结果直接明了。(Can realize classic spectral estimation and modern spectral estimation method , and performance results direct and clear. )

一个PCA的Matlab程序实例，应用于多维参数的自动降维和分类(The Matlab program example of a PCA applied to the automatic multi-dimensional parameter dimension reduction and classification)