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[Special Effects] GaussMRFandEMofImageSegmentation DL : 0: 2008年3月中国图象图形学报基于类自适应高斯-马尔可夫随机场模型和EM 算法的MR图像分割比较新的一片关于MARKOV以及EM算法的图像分割的文章。详细介绍了两种算法，以及对MR图像的实验结果，很有参考价值-March 2008 Journal of Image and Graphics of China based on the type of adaptive Gaussian- Markov random field model and the EM algorithm for MR image segmentation of a relatively new MARKOV as well as on the EM algorithm for image segmentation of the article. Two algorithms described in detail, as well as the experimental results of MR imaging is very useful
Update : 2025-04-04 Size : 262kb Publisher : luolunzi
[matlab] AFEM@matlab DL : 0: EM@matlab是一个有限元工具包，适用于静力和偏微分方程的演变-AFEM@matlab is a MATLAB package of adaptive finite element methods (AFEMs) for stationary and evolution partial differential equations in two spatial dimensions
Update : 2025-04-04 Size : 267kb Publisher : 晁忠贵
[AI-NN-PR] code DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2025-04-04 Size : 164kb Publisher : Binh
[File Format] EM DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2025-04-04 Size : 707kb Publisher : Binh
[File Format] lect26-em DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2025-04-04 Size : 232kb Publisher : Binh
[File Format] Lecture13 DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2025-04-04 Size : 72kb Publisher : Binh
[File Format] gmm_em_graphcut DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2025-04-04 Size : 1.14mb Publisher : Binh
[File Format] lec12 DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2025-04-04 Size : 47kb Publisher : Binh
[File Format] Documentation-fixed DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2025-04-04 Size : 2.38mb Publisher : Binh
[matlab] mixturecode2 DL : 0: 自适应的选择高斯混合模型个数，并用EM算法估计参数-Adaptive selection of the number of Gaussian mixture model and estimated parameters using EM algorithm
Update : 2025-04-04 Size : 10kb Publisher : ccj
[Special Effects] EM-like-algorithm-tracking DL : 0: 改进的meanShift算法，能够处理对象的旋转角度发生变化时的跟踪问题-An adaptive tracking algorithm,it s an improved MeanShift algorithm,can hanlde roation of the object during the tracking process
Update : 2025-04-04 Size : 6.85mb Publisher : joe
[AI-NN-PR] Adaptive-Embedding-Dimension DL : 0: 嵌入维数自适应最小二乘支持向量机状态时间序列预测方法 Condition Time Series Prediction Using Least Squares Support Vector Machine with Adaptive Embedding Dimension 针对航空发动机状态时间序列预测中嵌入维数难于有效选取的问题, 提出一种基于嵌入维数自适应最小二乘支持向量机( L SSVM ) 的预测方法。该方法将嵌入维数作为影响状态时间序列预测精度的重要参数, 以交叉验证误差为评价准则, 利用粒子群优化( P SO ) 进化搜索LSSV M 预测模型的最优超参数与嵌入维数, 同时通过矩阵变换原理提高交叉验证过程的计算效率, 并最终建立优化后的L SSVM 预测模型。航空发动机排气温度( EGT ) 预测实例表明, 该方法可自适应选取适用于状态时间序列预测的最优嵌入维数且预测精度高, 适用于航空发动机状态时间序列预测。- T o deal wit h the difficulty of selecting an appro pr iate embedding dimension for aeroeng ine co ndition time series predictio n, a metho d based o n least squar es suppo rt vecto r machine ( L SSVM ) with ada ptive em bedding dimension is pro po sed. I n the method, the embedding dimensio n is identified as a parameter that af fects the accuracy o f the aer oengine condition time series predictio n par ticle sw arm o ptimizat ion ( P SO) is ap plied to optimize the hyperpar ameter s and embedding dimension of the L SSV M pr edict ion model cro ssv alida tion is applied to evaluate the perfo rmance o f the L SSVM predictio n mo del and matr ix tr ansfo rm is applied to the L SSVM pr ediction model tr aining to accelerate the crossvalidation evaluation pro cess. Ex periments on an aeroengine ex haust g as t emperatur e ( EGT ) predictio n demonst rates that the metho d is hig hly effective in em bedding dimension selection. In compar ison w ith co nv
Update : 2025-04-04 Size : 334kb Publisher :
[JSP/Java] textareaAutoHeight-master DL : 0: textarea自适应高度插件: 使用方法: 0. 检查CSS文件中所有textarea的line-height值, 若是纯数字, 给它加上单位em, 如: 1.5em. 否则IE(6|7|8)下插件失效. 1. 加载jQuery库(1.4+) 2. 加载textareaAutoHeight.js 3. 使用以下接口调用插件: $( textarea ).tah({ moreSpace:15, //输入框底部预留的空白, 默认15, 单位像素 maxHeight:600, //指定Textarea的最大高度, 默认600, 单位像素 animateDur:200 //调整高度时的动画过渡时间, 默认200, 单位毫秒 }) -textarea height adaptive plug: use: check the CSS file for all the textarea line-height value, pure digital, plus it em, such as: 1.5em. otherwise IE (6 | 7 | 8) under plug failure. 1. loaded jQuery library (1.4+) 2 loaded textareaAutoHeight.js 3. use the following interface call plugin: $ (' textarea' ). tah ({moreSpace: 15,// input box at the bottom of reserved blank, the default 15 units of pixels maxHeight: 600,// Textarea maximum height specified, the default 600, the unit pixel animateDur: 200// adjust the height of the animation transition time, default 200 milliseconds})
Update : 2025-04-04 Size : 2kb Publisher : gpudn22
[Other] em DL : 0: em - EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2025-04-04 Size : 1kb Publisher : javidmehrnoosh
[Program doc] Algorithms_Signal_Processing DL : 0: 所上传为教程《信号处理的数学方法和算法》的配套代码。该书为读者和编程爱好者提供了广泛的应用于当代信号处理里面的数学工具。本书提供了分析，线性代数，优化，统计信号处理方面的扎实基础知识，以及配套算法代码。有趣的前沿课题包括了许多其他信号处理书籍里面的问题，比如，EM算法，盲源操作，凸集合的投影，等等，还包括许多常规的课题，比如谱估计，自适应滤波，等等。-Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear algebra, optimization, and statistical signal processing. Interesting modern topics not available in many other signal processing books such as the EM algorithm, blind source operation, projection on convex sets, etc., in addition to many more conventional topics such as spectrum estimation, adaptive filtering, etc.
Update : 2025-04-04 Size : 1.59mb Publisher : equalization
[Special Effects] em DL : 0: 自适应子集的em重建算法，是c程序，可以-The em reconstruction algorithm, adaptive subset is a c program, you can have a look
Update : 2025-04-04 Size : 5kb Publisher : 李权
[matlab] RLS自适应滤波器程序 DL : 0: RLS实现自适应滤波器的设计，)?令hM(-1)=0，计算滤波器的输出d(n)=XMT=hM(n-1)；?2)?计算误差值eM(n)=d(n)-d(n,n-1)；?3)?计算Kalman增益向量KM(n)；?4)?更新矩阵的逆RM-1(N)=PM(N)；?5)?计算hM(n)=hM(n-1)+KM(n)eM(n)；(Design of adaptive filter based on RLS)
Update : 2025-04-04 Size : 11kb Publisher : yin1995