matlabGUI

MATLAB相关的PPT 很齐全，讲解由浅入深，是初学者学习很好的资料。(MATLAB related PPT is complete, on the easy-to-digest, is very good information for beginners to learn.)

AM RECEIVER based on super heterodyne principle virtually used in all modern radio and television receivers. The approach mainly involves the use of heterodyning or frequency mixing. The signal from the antenna is filtered sufficiently at least to reject the image frequency and possibly amplified. A local oscillator in the receiver produces a sine wave which mixes with that signal, shifting it to a specific intermediate frequency (IF), usually a lower frequency. The IF signals is itself filtered and amplified and possibly processed in additional ways. The demodulator uses the IF signals rather than the original radio frequency to recreate a copy of the original modulation (such as audio). The project is coded in MATLAB.

MeanShift 代码的matlab实现(The implementation of mean shift by matlab)

2x2 alamouti code for mimo channel

The program implements the use of χ2 test for determining the distribution law of fluctuations of the signals. Hypotheses about the distribution of this or innogo parameter system, such as expectation, variance, probability density for a given level of significance accepted or refuted, in accordance with the results. The program implements two distributions: the exponential and Rayleigh.

Vehicle Serial Numbers ,and Money Value detection

matlab神经网络工具箱介绍，介绍了神经网络工具箱的函数使用(matlab neural network toolbox, the introduced neural network toolbox function of the use of)

modulation recognition documentation

implementation of NMPC control in matlab

：在有限区域内分布的稀疏不均的、具有一定分布结构的海量数据集的高效、高精度聚 类问题是一个尚未完全圆满解决的难题。针对Affinity Propagation 聚类算法(AP)的不足之处， 提出了两个改进型的聚类算法(n limited areas of uneven distribution of sparse, has certain distribution structure of the mass datasets of high efficiency, high precision together Problem is a perfectly solved problem has not yet completely. For Affinity Propagation clustering algorithm (AP) of the deficiencies, Put forward the two improved version of the clustering algorithm)