Gaussian mixture model or Gaussian mixture density model(GMM) uses the likelihood function as a measure of fit. We show that just the same algorithm as the GMM can be derived from a modified objective function of Fuzzy c-Means (FCM) clustering with the regularizer by K-L information, only when the parameter λ equals 2. Although the fixed-point iteration scheme of FCM is similar to that of the G...

In this paper wk have used two fuzzy clustering algorithms, namely Fuzzy C-Means (FCM) and Gustafson Kessel Clustering (GKC) for unsupervised change detection in multitemporal remote sensing images. In conventional FCM & GKC no spatio-contextual information is taken into account and thus the result is not so much robust to noise/outliers. By incorporation of local neighborhood informationthe pe...

With advances technologies of Internet and new digital image, the volume of digital images produced by scientific, educational, medical, industrial, and other applications has increased dramatically. The paper was inspired by symmetrical study about an image and also we tried to apply edge detection using Phase Congruency method that proposed by Kovesi. We tried making comparative study on edge...

We explore an approach to possibilistic fuzzy clustering that avoids a severe drawback of the conventional approach, namely that the objective function is truly minimized only if all cluster centers are identical. Our approach is based on the idea that this undesired property can be avoided if we introduce a mutual repulsion of the clusters, so that they are forced away from each other. We deve...

A Fick’s model that includes a Takagi-Sugeno fuzzy model to estimate the effective diffusivity was analyzed. The modelling of drying kinetics on mango trough this diffusional-fuzzy model was compared with the theoretical Fick’s model and the empirical Peleg and Weibull models. The identification and validation was performed from experimental drying curves of ripe mango slices (Mangifera indica ...

Two extensions to the objective function-based fuzzy clustering are proposed. First, the (point) prototypes are extended to hypervolumes, whose size can be fixed or can be determined automatically from the data being clustered. It is shown that clustering with hypervolume prototypes can be formulated as the minimization of an objective function. Second, a heuristic cluster merging step is intro...

Image segmentation is a process by which an image is partitioned into regions with similar features. Many approaches have been proposed for color image segmentation, but Fuzzy C-Means has been widely used, because it has a good performance in a large class of images. However, it is not adequate for noisy images and it also takes more time for execution as compared to other method as K-means. Fo...

Fuzzy time series forecasting methods do not require constraints found in conventional approaches. In addition, due to uncertainty that they contain, many time series to be forecasted should be considered as fuzzy time series. Fuzzy time series forecasting models consist of three steps as fuzzification, identification of fuzzy relations and defuzzification. Although most of the time series enco...

Thane Gustafson’s Wheel of Fortune: The Battle for Oil and Power in Russia is reviewed and situated within some broader trends in research on Russian natural resource extraction in the oil industry. Gustafson’s book represents the high water mark of a particular genre of scholarship on oil and considerably improves our understandings on a wide range of fronts. However, a number of other methodo...

We consider the dynamics of even solutions one-dimensional nonlinear Klein-Gordon equation $\partial_t^2 \phi - \partial_x^2 + |\phi|^{2\alpha} =0$ for $\alpha>1$, in vicinity unstable soliton $Q$. Our main result is that stability energy space $H^1(\mathbb R)\times L^2(\mathbb R)$ implies asymptotic a local norm. In particular, there exists Lipschitz graph initial data leading to stable and as...