support vector classification machine
％ soft margin
％ uses "kernel.m"
％
％ xtrain: (Ltrain,N) with Ltrain: number of points N: dimension
％ ytrain: (Ltrain,1) containing class labels (-1 or +1)
％ xrun: (Lrun,N) with Lrun: number of points N: dimension
％ atrain: alpha coefficients (from svcm_train on xtrain and ytrain)
％ btrain: offest coefficient (from svcm_train on xtrain and ytrain)
％
％ ypred: predicted y (Lrun,1) containing class labels (-1 or +1)
％ margin: (signed) separation from the separating hyperplane (Lrun,1
Prony算法工具箱。Prony方法是用一組指數項的線性組合來擬和等間距采樣數據的方法,可以從中分析出信號的幅值、相位、阻尼因子、頻率等信息。considerations including data preprocessing, model order selection, model order selection criteria, signal subspace selection, signal and noise separation, root inspection and assessing residuals. The PTbox provides flexibility to compare and display analysis results simultaneously for several parameter variations.
時間序列分析G-P method to calculate the correlation dimension of Matlab (Mex version) not use "temporary separation," use of the correlation integral Mex documents fast
I developed an algorithm for using local ICA in denoising multidimensional data. It uses delay embedded version of the data, clustering and ICA for the separation between data and noise.
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order
四種聚類算法源代碼及示例代碼,本程序的最終目的是形成一套標準的用于聚類、可擴展的工具。包括的內容有1. 聚類算法：Kmeans和Kmedoid算法、FCMclust, GKclust, GGclust算法 2. 評估分類原型：程序可以在二維圖像上繪制出聚類的結果 3. 驗證：程序給每一個算法提供驗證機制，每個聚類算法會統計Partition Coefficient (PC), Classification Entropy (CE), Partition Index (SC), separation Index (S), Xie and Beni s Index (XB), Dunn s Index (DI) and Alternative Dunn Index (DII)幾種衡量指標。
