Hamed Hamid Muhammed

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A new more efficient variant of a recently developed algorithm for unsupervised fuzzy clustering is introduced. A Weighted Incremental Neural Network (WINN) is introduced and used for this purpose. The new approach is called FC-WINN (Fuzzy Clustering using WINN). The WINN algorithm produces a net of nodes connected by edges, which reflects and preserves the(More)
A novel algorithm for unsupervised fuzzy clustering is introduced. The algorithm uses a so-called Weighted Fixed Neural Network (WFNN) to store important and useful information about the topological relations in a given data set. The algorithm produces a weighted connected net, of weighted nodes connected by weighted edges, which reflects and preserves the(More)
An automated method for the segmentation and tracking of moving vessel walls in 2D ultrasound image sequences is introduced. The method was tested on simulated and real ultrasound image sequences of the carotid artery. Tracking was achieved via a self organizing neural network known as Growing Neural Gas. This topology-preserving algorithm assigns a net of(More)
In this study, we present the exact solution of certain fractional partial differential equations (FPDE) by using a modified homotopy perturbation method (MHPM).The exact solutions are constructed by choosing an appropriate initial approximation and only one term of the series obtained by MHPM. The exact solutions for initial value problems of FPDE are(More)
A novel automated method for the classification of the physiological condition of the carotid artery in 2D ultrasound image sequences is introduced. Unsupervised clustering was applied for the segmentation process in which both spatial and temporal information was utilized. Radial distension is then measured in the inner surface of the vessel wall, and this(More)