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digital image processing using matlab..e-book

matlab 源码,基于小波变换的语音信息隐藏的实现,对原始语音信息和水印信息都经过三层小波分解处理后,将水印信息的低频信号嵌入原始语音信号的部分高频信号部分实现隐藏.源代码不仅给出隐藏过程,并且给出的在随机噪声,重采样,信息压缩情况下的抗攻击特性.源代码清晰有注释(matlab source code, based on wavelet transform voice messages hidden realize, the original voice information and watermark information after a three-treatment, after wavelet decomposition, the watermark information embedded in the low-frequency signals of the original speech signal realize some hidden part of high-frequency signals. source code is given not only to hide the process, and given in random noise, resampling, compression of information in case of anti-attack features. source code has a clear Notes)

完成输入序列的msk调制功能，输入序列必须是0 1(Complete input sequence of msk modulation, the input sequence must be 01)

MATLAB实现模糊神经网络算法， 包括训练函数和测试函数的MATLAB代码，并具有运用案例。很适应。(MATLAB realization of fuzzy neural network algorithm, including training function and test function of the MATLAB code, and has a use case. Very fit.)

信号与系统基础练习，演示了数字信号处理中常用的傅里叶变换，分析时域和频域的信息(Signals and systems based practice, demonstration of digital signal processing used in the Fourier transform of the time domain and frequency domain information analysis)

matlab 数值分析 书中代码详解 齐全 例题和答案都有(Detailed numerical analysis book matlab code examples and answers have complete)

rand, randn, randint.... you can understand my code

核主元分析和支持向量机结合的故障诊断方法(KPCA and SVM fault diagnosis method combining)

说明：  一种基于角点信息和透视变换的图像镶嵌源代码(A corner-based information and perspective transformation of the image mosaic source code)

为实现合成孔径雷达（SAR）图像分类算法的测试与评估，将VC/Matlab 混合编程技术应用到SAR 图像分类平台开发中，分析与 比较了4 种VC/Matlab 混合编程方法及各自优缺点，并着重研究了基于组件对象模型（COM）的VC/Matlab 混合编程方法。使用Matlab COM 编译器创建了SAR 图像分类算法组件，在VC 中调用其导出的接口函数。在此基础上，完成了SAR 图像分类平台的实例开发且 可脱离Matlab 环境运行。实验结果表明，该方法较好地发挥了VC 与Matlab 各自的优势，提高了SAR 图像分类平台开发的效率。(In order to test synthetic aperture radar （SAR） image classification algorithm，VC/Matlab mixed programming technology was used in SAR image classification platform development. Four VC/Matlab mixed programming methods were introduced and analyzed. Comparing with other three methods，the method based on component object model （COM） was studied particularly. SAR image classification algorithm component was created by Matlab COM complier，and its interface function could be invocated with VC. Using this method，a SAR image classification platform was realized. The platform could run without Matlab. The experimental result shows a good combination of VC and Matlab. So，developing efficiency could be enhanced a lot.)