Golub_and_Van_Loan.Matrix_computations.pdf

Discriminant Analysis tutorial for toolbox

卡尔曼滤波跟踪改进算法,这种算法在原来的基础上进行改进，能够更好地实现其跟踪的过程。(the improvement of Kalman filtering s tracking algorithm)

基于序贯蒙特卡洛采样的粒子滤波程序，主要实现机动目标的跟踪，并给出噪声分析(target Tracking based on SMC PF)

此为基于二代提升小波的阈值压缩算法源码，其中可以设置小波变换的分解层数，使用的小波名称，及各层阈值设置计算公式中的参数。并将低频系数转化为十六进制，方便在其上进一步压缩，如采用Huffman压缩等，程序思路清楚，附有完整的注释，可以使用多种小波，并且很好得体现了二代小波的思想，对于初学小波者帮助很大。(based on the second generation of this upgrade wavelet compression algorithm threshold source, which can set wavelet transform decomposition level, the use of wavelet name, threshold levels and set the formula for calculating the parameters. And low-frequency coefficients into hexadecimal facilitate its further compression, such as the Huffman compression. procedures ideas clearly, with the integrity of the Notes, you can use a variety of wavelet, and reflected very well in the second generation wavelet thinking, For beginners who wavelet of great help.)

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Basics of wavelet function

在这项工作中所使用的方法是基于一个由大卫阿诺德教程。 http://online.redwoods.cc.ca.us/instruct/darnold/diffeq/logistic/logistic.pdf 这将运行该Logistic.m带来了图形用户界面。 1。放弃在列的格式文本文件中的x值 2。放弃在山口格式文本文件中的y值 3。的阴谋初始 按钮将绘制的分布 4。 查找适合 按钮，会找到最适合 5。 重置 将删除的情节（虽然我想打扫所有的领域 -没有时间） 5。地下K，糖尿病在下列公式中的值 Ÿ 等于k/（1+进出口（- G *的（十型录））） 6。上证所给出了squred误差之间的拟合函数与实际数据的总和 7。消委会提供的相关合作关系的实际数据拟合功能和效率(The method used in this work is based on a tutorial by David Arnold. http://online.redwoods.cc.ca.us/instruct/darnold/diffeq/logistic/logistic.pdf RUN The Logistic.m this will bring up the GUI. 1. Give the x values on a text file in column format 2. Give the y values on a text file in col format 3. Plot Initial Button will plot the distribution 4. Find Fit button will find the best fit 5. Reset will remove the plot (Although I wanted to clean all the fields- did not have time) 5. K, G, Dm are the values in the following equation y = K./(1+exp(-G*(x-Dm))) 6. SSE gives the sum of squred error between the fitted function and the actual data 7. CC give the correlation co-efficient between the fitted function and actual data)

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BURG方法谱估计 采用BURG迭代方法计算系数，在采用AR模型的谱估计进行谱峰搜索(BURG spectrum estimation methods BURG iterative method using coefficients in the AR model spectrum estimation using the peak search)

基于二阶导数的图像边缘检测方法，包括marr算法和laplacian算法(Second derivative-based edge detection methods, including marr algorithms and laplacian algorithm )