Given a finite configuration of points in a metric space, a Steiner center (respectively, a centroid) is the point of the space (respectively, of the configuration) that minimizes the sum of the distances from all its elements. Working on the k-dimensional real space endowed with the Manhattan distance, we study the approximate algorithm that takes a point of minimum distance from the Steiner c...

In recent years, the eeect of the curse of high dimensionality has been studied in great detail on several problems such as clustering, nearest neighbor search, and indexing. In high dimensional space the data becomes sparse, and traditional indexing and algorithmic techniques fail from a eeciency and/or eeectiveness perspective. Recent research results show that in high dimensional space, the ...

Texture can be observed in many natural and synthetic images from multispectral satellite images to the microscopic images of cell or tissue samples. Texture is an innate property of virtually all surfaces, the grain of wood, the weave of fabric, the pattern of crop in fields etc It contains important information about the structural arrangement of surfaces and their relationship to the surroun...

Abstract The fuzzy k-nearest neighbor (FKNN) algorithm, one of the most well-known and effective supervised learning techniques, has often been used in data classification problems but rarely regression settings. This paper introduces a new, more general model. Generalization is based on usage Minkowski distance instead usual Euclidean distance. not optimal choice for practical problems, better...

One of the numerous methods recently employed to study the health of structures is the identification of anomaly in data obtained for the condition of the structure, e.g. the frequencies for the structural modes, stress, strain, displacement, speed,  and acceleration) which are obtained and stored by various sensors. The methods of identification applied for anomalies attempt to discover and re...

In recent years, the effect of the curse of high dimensionality has been studied in great detail on several problems such as clustering, nearest neighbor search, and indexing. In high dimensional space the data becomes sparse, and traditional indexing and algorithmic techniques fail from a efficiency and/or effectiveness perspective. Recent research results show that in high dimensional space, ...

The general Robot Motion Planning Problem, to nd a collision-free path from a given start position to a given goal position amidst obstacles, can be extended in several ways, e.g. by taking into account kinematics and dynamic constraints, by allowing obstacles to move slightly, by asking for a path that can be seen as a good pay-oo between safest and shortest path, by planning with uncertainty,...

The paper presents an analog, current-mode circuit that calculates a distance between the neuron weights vectors W and the input learning patterns X. The circuit can be used as a component of different self-organizing neural networks (NN) implemented in the CMOS technology. In Self-Organizing Maps (SOM) as well as in NNs using the Neural Gas or the Winner Takes All (WTA) learning algorithms, to...

Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent t...