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MatLab Engineering Mathematics about Mathematics and application

说明：  卡尔曼滤波和自适应滤波 y(Kalman filtering and adaptive filtering y)

m序列生成和抽取，Gold码和kasami序列生成，三种序列子相关，互相性能分析等。程序完整，注释清楚，报告详细。(m sequence generation and extraction, Gold codes and kasami sequence generation, all three sub-sequences related to each other performance analysis. Program integrity, comments clear, the report detailed.)

用MATLAB编写的混沌序列图像加密程序，密钥可以从0到1之间的任何一个数(MATLAB prepared by the chaotic sequence image encryption program, the key can be any number 0 to 1)

基于bp神经网络的汽车牌照识别matlab源程序文件(network recognized)

help full code for coded OQAM OFDM

ASM是由Cootes和泰勒推出的多分辨率方法的一个例子。 基本思想： 在ASM模型训练，训练从手工绘制的图像轮廓。发现的ASM模型在训练使用主成分分析（PCA），使该模型自动识别数据的主要变化是，如果可能的轮廓/好的对象的轮廓。还包含了ASM模型的协方差矩阵描述行垂直纹理口岸时，在正确的位置。 (Description This is an example of the basic Active Shape Model (ASM) as introduced by Cootes and Taylor, with multi-resolution approach. Basic idea: The ASM model is trained from manually drawn contours in training images. The ASM model finds the main variations in the training data using Principal Component Analysis (PCA), which enables the model to automatically recognize if a contour is a possible/good object contour. Also the ASM models contains covariance matrices describing the texture of the lines perpendicular to the control points when in the correct positions. After creating the ASM model, an initial contour is deformed by finding the best texture match for the control points. This is an iterative process, in which the movement of the control points is limited by what the ASM model recognizes from the training data as a "normal" object contour. Literature: - Ginneken B. et al. "Active Shape Model Segmentation with Optimal Features", IEEE Transactions on Medical I)

linear time－frequency toolbox(linear time-frequency toolbox)

using L in profile storage. We may solve Ly  b accessing L by row and either LTx  y accesing LT by column or equivalently xTL  yT accessing L by row

ASK Modulation using MATLAB