Kernel trick is a powerful tool being used for solving complex pattern classification problem. As long as a linear feature extraction algorithm can be expressed exclusively by dot-products, it can be extended to non-linear version by combining kernel method. In this paper, we present such an improved iterative algorithm used for linear discriminant analysis. By mapping data onto high dimensiona...

De novo structure determination of proteins is a significant research issue of bioinformatics. Biochemical procedures for protein structure determination are costly. Use of different pattern classification techniques are proved to ease this task. In this article, the secondary structure prediction task has been mapped into a three-class problem of pattern classification, where the classes are h...

In this paper, a novel approach, namely nonlinear subprofile space (NSS), is proposed for radar target recognition using high-resolution range profile (HRRP). First, the HRRP samples are mapped into a high-dimensional feature space using nonlinear mapping. Second, the nonlinear features, namely nonlinear subprofiles, are extracted by nonlinear discriminant analysis. Then, for each class, the no...

This paper presents classification of various land cover types from the raw satellite image using supervised classifiers and performances of the classifiers are analyzed. Geo coded and Geo-referenced remote sensed images from Survey of India, Government of India Topographical maps are used. Prior to classification, Training process to assemble a set of statistics describing spectral response pa...

Abstract For a graph G , and two distinct vertices u v of let $$n_{G}(u,v)$$ n G ( u , v ) be the number that are closer in to than . Miklavi? Šparl (arXiv:2011.0...