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kmeans
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.
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9927412matlab111
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变采样点范围能够改善输出光强的结果逼真程度。(一束光through a transparent cylinder, a cylindrical post-screen process will ultimately reflect the on-screen image with the cylindrical radius change. Light intensity distribution of which is the principle of coherent superposition, because the insufficient number of sampling points, so light intensity distribution of the results and have some real gaps. Increase in the number of sampling points and to change the scope of sampling points can improve the outcome of the output light intensity the degree of realism.)
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MATLAB--lizi
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EWT
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mcbyq
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work_kalman
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