Vector quantization (VQ) is widely used in many applications, ranging from image and speech coding to pattern recognition. The authorse propose a method for using the covariance matrix of the individual clusters as the basis for grouping. In this algorithm, the Mahalanobis distance is used as a measure of similarity in each cluster. Properties of the new clustering method are presented by examining the clustering quality for codebooks designed with the proposed method and two competing methods on a variety of data sets. The competing methods are the Linde-Buzo-Gray (LBG) algorithm and the fuzzy c-means (FCM) algorithm using Euclidean distance. The new method provides better results than the competing methods for several data sets. Thus, this method becomes another useful tool for use in codebook design.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Vector quantization based on dynamic adjustment of Mahalanobis distance


    Beteiligte:
    Younis, K.S. (Autor:in) / Rogers, S.K. (Autor:in) / DeSimio, M.P. (Autor:in)


    Erscheinungsdatum :

    01.01.1996


    Format / Umfang :

    675959 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Vector Quantization Based on Dynamic Adjustment of Mahalanobis Distance

    Younis, K. S. / Rogers, S. K. / DeSimio, M. P. et al. | British Library Conference Proceedings | 1996


    Mahalanobis Distance Method for Unclassifiable Region of Support Vector Machine

    Li, R. / Li, A. / Wang, T. et al. | British Library Online Contents | 2010


    Directional Mahalanobis Distance and Parameter Sensitivities

    Chinta, Balakrishna | British Library Conference Proceedings | 2016


    Directional Mahalanobis Distance and Parameter Sensitivities

    Chinta, Balakrishna | SAE Technical Papers | 2016


    An adaptive fading Kalman filter based on Mahalanobis distance

    Chang, Guobin / Liu, Ming | SAGE Publications | 2015