GSM2

多载波的采用二进制移相键控BPSK调制的性能matlab仿真(none)

Soure for fault classification using machine intelligence technique

1.Matlab 7.6简单入门。 2.Matlab 7.6小波工具入门。(1.Matlab 7.6 simple tutorial. 2.Matlab 7.6 Introduction of wavelet tools.)

park transformation using simulink blocks

【matlab编程代做】MATLAB实现M-QAM调制解调演示源代码 ([Do] matlab MATLAB Programming generation M-QAM modulation and demodulation realize demo source code can refer to the use of)

OFDMA上行链路的模拟程序，可能有一些小BUG(OFDMA uplink simulation program, there may be some small BUG)

一些失量量化码书设计的方法总结，包含全面，用matlab编程的(Some loss of quantization codebook design methods are summarized, including comprehensive programming using matlab)

Multisensor image fusion has its effective utilization for surveillance. In this paper, we utilize a pulse coupled neural network method to merge images different sensors, in order to enhance visualization for surveillance. On the basis of standard mathematical model of pulse coupled neural network, a novel step function is adopted to generate pulses. Subjective and objective image fusion performance measures are introduced to assess the performance of image fusion schemes. Experimental results show that the image fusion method using pulse coupled neural network is effective to merge images different sensor

说明：  相场模型的经典教程，包含MATLAB源代码说明，适合新手(the classic tutorial of Phase field modeling , including Matlab source code description, suitable for junior programmer)

说明：  复杂网络研究与建模 总起来说这是一个关于矩阵的运算，用到了c语言里面的东西，实现一个矩阵的逆运算和矩阵的转置等，最终实现的是一个初始节点为4个节点的有向图，随即扩展为一个10000*10000的巨型矩阵，得到该有向图的图形， 与计算机图形学类似，该程序是在构建了一个算法后，用MATLAB实现了一个无标度网络的图形中的各个节点的概率密度，并根据各个节点的概率密度绘出该图 (将中文译成英语 And modeling complex networks Collectively this is a computation on the matrix, use the stuff inside c language to realize the inverse of a matrix and a matrix, etc., and ultimately is an initial node to four nodes directed graph, then Expands to a huge matrix 10000* 10000, by the digraphs graphics, And similar computer graphics, the program is built upon an algorithm, using MATLAB to achieve a scale-free network each node in the graph the probability density and probability density according to each node in the graph drawn )