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MATLAB 实现回归分析及逐步回归及预测 可用于数学建模(MATLAB)

MATLAB function which creates a black and white version of a grayscale image by specifying a single threshold value pixels below this value become black, and above this value they are white. Usage:

function [L,C] = kmeans(X,k) KMEANS Cluster multivariate data using the k-means++ algorithm. [L,C] = kmeans(X,k) produces a 1-by-size(X,2) vector L with one class label per column in X and a size(X,1)-by-k matrix C containing the centers corresponding to each class. Version: 07/08/11 Authors: Laurent Sorber (Laurent.Sorber@cs.kuleuven.be) References: [1] J. B. MacQueen, "Some Methods for Classification and Analysis of MultiVariate Observations", in Proc. of the fifth Berkeley Symposium on Mathematical Statistics and Probability, L. M. L. Cam and J. Neyman, eds., vol. 1, UC Press, 1967, pp. 281-297. [2] D. Arthur and S. Vassilvitskii, "k-means++: The Advantages of Careful Seeding", Technical Report 2006-13, Stanford InfoLab, 2006.

Power Spectrum Estimation

matlabiir巴特沃斯低通数字滤波器(matlab iir butterworth low-pass digital filter)

AC MOTOR ACTUATOR OPERATING POINTS

Implemenation of a variant of the rotation forest (Rodriguez et al., Rotation Forest: a new classifier ensemble method, PAMI 2006) proposed in L. Nanni and A. Lumini, Using ensemble of classifiers in Bioinformatics, in H. Peters and M. Vogel, Machine Learning Research Progress, Nova publisher, 2009

元胞自动机 实现金属氧化过程 很实用的 (The cellular automata metal oxidation)

最大流问题，一种组合最优化问题，就是要讨论如何充分利用装置的能力，使得运输的流量最大，以取得最好的效果。求最大流的标号算法最早由福特和福克逊于1956年提出，20世纪50年代福特、福克逊建立的“网络流理论”，是网络应用的重要组成成分。(Maximum flow problem, a combinatorial optimization problem, is to discuss how to make full use of the capacity of the device to maximize the flow of transport in order to achieve the best results. The labeling algorithm for maximum flow was first proposed by Ford and Fulkerson in 1956. The network flow theory established by Ford and Fulkerson in 1950s is an important component of network application.)

对室内的行人定位跟踪算法进行研究：包括基于RSS的KNN室内定位算法、基于RSS的卡尔曼滤波算法、融合RSS和DR的粒子滤波算法 等。(indoor pedestrian position tracking algorithm is studied, such as the KNN localization algorithm based on the RSS, the kalman filter algorithe based on the RSSthe particle filter algorithm which is fusion of RSS DR and Map information.)