cs-sarcosamp

cocos 2d sample using simple tile operations.

对信号进行小波包分解并求取各个分量的功率谱(The signal wavelet packet decomposition and obtain the power spectrum of the various components)

此为基于MATLAB平台计算指纹图像中两点之间穿越纹线数(For fingerprint processing is calculated through the ridge)

sar-sp-matlab小程序sar-sp-matlab小程序sar-sp-matlab小程序sar-sp-matlab小程序(sar-sp-matlab applet sar-sp-matlab applet sar-sp-matlab applet sar-sp-matlab applet)

Matlab接收串口的数据，并作出相应的处理(Matlab receive serial data and processing it )

ofdm调制方式识别的matlab仿真程序，即ofdm信号与单载波信号之间的识别，利用的是高阶累积量作为特征参数(Ofdm modulation mode recognition of matlab simulation program, that is, between ofdm signal with single carrier signal recognition, using the high-order cumulants as characteristic parameters)

这是一份MATLAB基础课件，由于我也是初学者，这部课件讲的很浅显，但比较适合初学者对MATLAB所有功能的一个初步了解内容包括涵数值数组及其运算， M文件和面向对象编成， 字符串数组， 符号变量， matlab 绘图 及 Simulnk动态仿真。以及两个基本浅显的程序题。此为第 5章。(This is a basic MATLAB courseware, because I am also a beginner, this software is very simple-speaking, but more suitable for beginners of all the features of MATLAB, a preliminary understanding of the content including the Han and its numerical array computing, M documents and for object into string array, variable symbols, matlab graphics and dynamic simulation Simulnk. As well as the two basic procedures for simple questions. This is Chapter 5.)

介绍了Ｍａｔｌａｂ的神经网络算法，对具体的事列进行了分析和计算。(Introduction of the Matlab neural network algorithms, on specific matters set out an analysis and calculation.)

各种颜色空间介绍(Introduced a variety of color space)

GM(1,1)模型1-4 1：GM(1,1)模拟模型，在matlab中的输入方法为gm1（x），x指要模拟的序列。 2：GM(1,1)预测模型，在matlab中的输入方法为gm2（x，K），x指要模拟的序列，K指从以后序列第一个数据算起的第k个待预测数据。 3：GM(1,1)群模拟模型，在matlab中的输入方法为gm3（x），x指要模拟的序列。 4：GM(1,1)群预测模型，在matlab中的输入方法为gm4（x，K），x指要模拟的序列，K指从以后序列第一个数据算起的第k个待预测数据。 gm4对序列趋势比较好的数据预测效果较好，对上下变动的数据，特别是后4个数据趋势跟前面的数据相反的，预测效果很差。 gm2对上下变动的数据，预测效果比gm4好，但对趋势较好的数据，预测精度没有gm4高。 gm3比gm1模拟精度要高。 可以以x=[1 3 5 7 9 11 13 15]进行实验。x输入默认行向量。 所有程序在matlab6.0上调试通过。(GM (1,1) 1-4 1 : GM (1,1) simulation model Matlab in the input method for gm1 (x), x entail simulation sequence. 2 : GM (1,1) model, in the Matlab input method for gm2 (x, K), x entail simulated sequence, from the K refers to the first series after a run of data k pending forecast data. 3 : GM (1,1)- simulation model, in the Matlab input method for gm3 (x), x entail simulation sequence. 4 : GM (1,1)- forecasting model, in the Matlab input method for gm4 (x, K), x entail simulated sequence, from the K refers to the first series after a run of data k pending forecast data. Gm4 right sequence relatively good trend data predicted better results, the next change in the data, especially after four data with the previous trend data contrary, predict poor. Gm2 next to the change in forecast resu)