Clustering is a fundamental data analysis method. It is widely used for pattern recognition, feature extraction, vector quantization (VQ), image segmentation, function approximation, and data mining. As an unsupervised classification technique, clustering identifies some inherent structures present in a set of objects based on a similarity measure. Clustering methods can be based on statistical...

In this paper a new pattern recognition methodology is described for the classification of the daily chronological load curves of power systems, in order to estimate their respective representative daily load profiles, which can be mainly used for load forecasting and feasibility studies of demand side management programs. It is based on pattern recognition methods, such as k-means, adaptive ve...

this paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. in this method, mammograms are segmented into regions of interest (roi) in order to extract features including geometrical and contourlet coefficients. the extracted features benefit from...

In parametric speech coding, the accuracy of parameter quantization has a significant effect on speech quality. In this paper, we present a flexible and high-fidelity multi-mode quantization approach that combines the beneficial features of predictive vector quantization and matrix quantization. As an example, the proposed technique is employed in quantization of the power component in a wavefo...

Two new extensions of Fuzzy C-means (FCM) algorithm which minimize an objective function incorporating a validity index are proposed. These algorithms are applied to color quantization of images. In the first approach, we minimize an objective function including a term for partition index. This algorithm attempts to place the cluster centers such that the membership values of the pixels are max...

<span>The Indonesian government often needs assistance in making citizen-based decisions, for example selecting work program plans. Residents have their criteria the forum to choose a plan. This study proposes K-means fuzzy learning vector quantization (FLVQ) methods select decision-making criteria. The FLVQ method has never been used assist decision-making. However, citizen can be succes...