This tutorial provides a concise overview of support vector machines and different closely
related techniques for pattern classification. The tutorial starts with the formulation of support …

This paper presents a comprehensive review of hybrid and ensemble-based soft computing
techniques applied to bankruptcy prediction. A variety of soft computing techniques are …

In this paper, a generalized formulation for intelligent energy management of a microgrid is
proposed using artificial intelligence techniques jointly with linear-programming-based …

In this paper we apply a recently proposed technique of optimal control by support vector
machines (SVMs) to chaos control. Vapnik's support vector method, which is based on the …

Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

A brain–computer interface (BCI) is a communication system that translates brain-activity
into commands for a computer or other devices. In other words, a BCI allows users to act on …

Abstract In Support Vector Machines (SVMs), the solution of the classification problem is
characterized by a (convex) quadratic programming (QP) problem. In a modified version of …

Location-awareness is becoming increasingly important in wireless networks. Indoor
localization can be enabled through wideband or ultra-wide bandwidth (UWB) transmission …

Traditionally, the hinge loss is used to construct support vector machine (SVM) classifiers.
The hinge loss is related to the shortest distance between sets and the corresponding …

This paper examines the theory of kernel Fisher discriminant analysis (KFD) in a Hilbert
space and develops a two-phase KFD framework, ie, kernel principal component analysis …