The paper solves the eigenvalues of a symmetric matrix by using three novel algorithms developed in m-dimensional affine Krylov subspace. n-dimensional eigenvector is superposed constant shifting vector and an m-vector. In first algorithm, m-vector derived as function eigenvalue maximizing Rayleigh quotient to generate characteristic equation, which, however, not easy determine since its roots ...

Singular value decomposition (SVD) is a useful multivariate technique for dimension reduction. It has been successfully applied to analyze microarray data, where the eigen vectors are called eigen-genes/arrays. One weakness associated with the SVD is the interpretation. The eigen-genes are essentially linear combinations of all the genes. It is desirable to have sparse SVD, which retains the di...

The current research paper is an implementation of Eigen Faces and Karhunen-Loeve Algorithm for face recognition. The designed program works in a manner where a unique identification number is given to each face under trial. These faces are kept in a database from where any particular face can be matched and found out of the available test faces. The Karhunen –Loeve Algorithm has been implement...

This paper introduces the concept of eigen-dynamics and proposes an eigen dynamics analysis (EDA) method to learn the dynamics of natural hand motion from labelled sets of motion captured with a data glove. The result is parameterized with a high-order stochastic linear dynamic system (LDS) consisting of five lower-order LDS. Each corresponding to one eigen-dynamics. Based on the EDA model, we ...

As is widely-known, the eigen-functions of Landau problem in symmetric gauge are specified by two quantum numbers. The first familiar number $n$, whereas second magnetic $m$, which eigen-value canonical orbital angular momentum (OAM) operator electron. eigen-energies system depend only on and $m$ does not correspond to any direct observables. This seems natural since OAM generally believed be a...

People employ the function-on-function regression to model relationship between two stochastic processes. Fitting this model, widely used strategies include functional partial least squares algorithms which typically require iterative eigen-decomposition. Here we introduce a route of based upon Krylov subspace. Our can be expressed in forms equivalent each other exact arithmetic: One is non-ite...

Method for face identification based on eigen value decomposition together with tracing trajectories in the eigen space after the eigen value decomposition is proposed. The proposed method allows person to person differences due to faces in the different emotions. By using the well known action unit approach, the proposed method admits the faces in the different emotions. Experimental results s...

IV. Quantum anomalous Hall effect in a T -violating topological insulator model 10 A. 1d model 10 B. 2d model 12 C. Quantized Hall conductivity of the 2d bulk system topological invariant 13 1. Bulk eigen-states 13 2. Coupling to an external constant electric field Adiabatic eigen-states 14 3. Time-dependent perturbation theory based on adiabatic eigen-states 14 4. Adiabatic current 15 5. Hall ...

We exhibit a stochastic discrete time model that has the Eigen model as its deterministic continuous limit. Such model can be divided into two phases: reproduction followed by neutral selection. This result suggests that Eigen model describes the competition among individuals differing for reproductive capability but equivalent as survivors. We explicitly write down the Markov matrix of the sto...

Sign Language Recognition is one of the most growing fields of research today. Many new techniques have been developed recently in these fields. Here in this paper, we have proposed a system using Eigen value weighted Euclidean distance as a classification technique for recognition of various Sign Languages of India. The system comprises of four parts: Skin Filtering, Hand Cropping, Feature Ext...