In this paper, a fast bounded parametric margin  -support vector machine (BP- SVM) for classification is proposed. Different from the parametric margin  -support vector machine (par- -SVM), the BP- -SVM maximizes a bounded parametric margin, and consequently the successive overrelaxation (SOR) technique could be used to solve our dual problem as opposed solving the standard quadratic progr...

A tool for diagnosis assistance by automatic segmentation of microscopic cellular images is introduced. This method is based on an automatic segmentation technique combining (with the Dempster-Shafer rule) the results obtained by Support Vector Machines (SVM) applied within different color spaces. This combination is performed by integrating uncertainties and redundancies for each color space. ...

We propose an algorithm to do speech/non-speech classification based on low-rank matrix representative audio data. Conventionally, the low-rank matrix data can be represented by a vector in high dimensional space. Some learning algorithms are then applied in such a vector space for matrix data classification. Particularly, maximum margin classifiers, such as support vector machine (SVM) etc. ha...

Multivariate data analysis techniques have the potential to improve data analysis. Support Vector Machines (SVS) are a recent addition to the family of multivariate data analysis. A brief introduction to the SVM Vector Machines technique is followed by an outline of the practical application Key-Words: SVM vector machines, data analysis

This paper studies the problem of building Web page classifiers using positive and unlabeled examples, and proposes a more principled technique to solving the problem based on tolerance rough set and Support Vector Machine (SVM). It uses tolerance classes to approximate concepts existed in Web pages and enrich the representation of Web pages, draws an initial approximation of negative example. ...

We investigate constrained first order techniques for training Support Vector Machines (SVM) for online classification tasks. The methods exploit the structure of the SVM training problem and combine ideas of incremental gradient technique, gradient acceleration and successive simple calculations of Lagrange multipliers. Both primal and dual formulations are studied and compared. Experiments sh...

The implementation and analysis strategies plays vital role to minimize THD in Multilevel inverter. The modulation technique regards Selective harmonic Elimination and Space Vector Pulse Width Modulation(SVPWM).Multilevel inverters has tremendous application in the area of high-power and mediumvoltage energy control. In this paper simulation of SVPWM is performed for cascaded H bridge Multileve...

Volume 1, Number 1, June 2010 9 May 2010 Abstract – This paper presents a power loss minimization technique for a cascaded multilevel inverter using hybrid carrier based space vector modulation. The proposal in this paper combines the features of carrier based space vector modulation and the fundamental frequency modulation strategy. The main characteristic of this modulation is the reduction o...