EKMEANS - Euclidean k-Means Clustering Algorithm 
    EKMEANS clusters a term-document matrix using the standard 
    k-means clustering algorithm. CLUSTERS=EKMEANS(A, C, K, 
    TERMINATION) returns a cluster structure with K clusters 
    for the term-document matrix A using as initial centroids 
    the columns of C (initialized randomly when it is empty). 
    TERMINATION defines the termination method used in k-means 
    ('epsilon' stops iteration when objective function decrease 
    falls down a user defined threshold - see OPTIONS input 
    argument - while 'n_iter' stops iteration when a user 
    defined number of iterations has been reached). 
    [CLUSTERS, Q]=EKMEANS(A, C, K, TERMINATION) returns also
    the vector of objective function values for each iteration 
    and [CLUSTERS, Q, C]=EKMEANS(A, C, K, TERMINATION) returns 
    the final centroid vectors. 
    EKMEANS(A, C, K, TERMINATION, OPTIONS) defines optional 
    parameters: 
        - OPTIONS.iter: Number of iterations (default 10).
        - OPTIONS.epsilon: Value for epsilon convergence 
          criterion (default 1).
        - OPTIONS.dsp: Displays results (default 1) or 
          not (0) to the command window.
 
  Copyright 2011 Dimitrios Zeimpekis, Eugenia Maria Kontopoulou, 
                 Efstratios Gallopoulos