mallat-for-signal-process

是一篇关于复杂网络的论文这个文档还是有点价值的(Is a complex network of papers on this document is still a bit value of)

说明：  BP算法客运量预测，十分详细的好资料，值得参考(Passenger Volume Forecast BP algorithm, a very good detailed information, it is also useful)

精密单点定位的程序，是对初学者的很好的资料，很容易入手(Precise point positioning procedure ，is good information for beginners, it is easy to start)

matlab based edge detection method

说明：  matlab simulink about a theory jame machin

雷达成像经典教材，保铮邢孟道著，适合入门新手(Radar Imaging classic textbook, Bao Zheng Xing Meng-dao with, for entry-novices)

这是一个基于空时分组编码的MIMO_OFDM通信系统的仿真设计。此系统包括QPSK调制解调，IFFT调制，空时编解码，基于训练符号的信道估计等通信模块。(This is a space-time block codes based on the MIMO_OFDM Communication System Simulation and Design. This system consists of QPSK modulation and demodulation, IFFT modulation, space-time coding and decoding, based on training symbols such as communication channel estimation module.)

matlab编写的遗传算法，采用二进制编码，有说明文档。(Matlab prepared by the genetic algorithm, using the binary coding, documentation.)

emd分解是对原始信号分解得到各个分量的过程，它的核心是通过找出信号的极大值和极小值点拟合出上下包络从而得到平均包络。(The emd decompose each component of the process of decomposition of the original signal, its core is by identifying the maximum and minimum points of the signal fitting upper and lower envelopes in order to get the average envelope.)

相关向量机(RVM)的matlab源程序，包含快速算法，内含代码使用说明。 RVM采取是与支持向量机相同的函数形式稀疏概率模型，对未知函数进行预测或分类。 优点： (1) 不仅仅输出预测目标量的点估计值,还可以输出预测值的分布. (2) 使用更少数量的支持向量,从而显著减少输出目标量预测值的计算时间. (3) RVM不需要估计过多的参数. (4) RVM对是否满足Mercer 定理的核函数没有限制,适应性更好(Relevance Vector Machine (RVM) of the matlab source code, including fast algorithm that contains code for use. RVM support vector machine is taken the same functional form sparse probabilistic model to predict the unknown function or classification. Advantages: (1) is not only the amount of output predicted target point estimates, but also the distribution of predicted values ​ ​ can be output. (2) using a smaller number of support vectors, thereby significantly reducing the output target amount predicted value calculation time. (3) RVM does not require excessive parameter estimation. (4) RVM meets Mercer theorem on the kernel function is not limited, and better adaptability)