Eigenvectors and eigenvalues are numbers and vectors associated to square matrices, and together they provide the eigen-decomposition of a matrix which analyzes the structure of this matrix. Even though the eigen-decomposition does not exist for all square matrices, it has a particularly simple expression for a class of matrices often used in multivariate analysis such as correlation, covarianc...

Water-filling is the power allocation that maximizes the parallel-channel eigen-MIMO informationtheoretic capacity. However, for practical designs, designing for error performance is also important. The overall uncoded error rate, in a system with water-filled eigen-channels using digital modulation, degrades through the errors in the data that uses the weaker eigen-channels. This is because in...

In this paper, the numerical solution methods of one- particale, one – dimensional time- independentSchrodinger equation are presented that allows one to obtain accurate bound state eigen values andeigen functions for an arbitrary potential energy function V(x). These methods included the FEM(Finite Element Method), Cooly, Numerov and others. Here we considered the Numerov method inmore details...

Aljabar max-plus adalah suatu struktur aljabar yang dilengkapi dengan operasi maksimum dan penjumlahan. Diantara beberapa masalah pada menentukan nilai eigen vektor matriks atas max-plus. Nilai dapat diterapkan dalam keperiodikan sistem antrian. Dalam tulisan ini akan dibahas penentuan eigen, serta aplikasinya keperidikan dicari berdasarkan bobot rata-rata sirkuit elementer graf terkait digunak...

in this paper, the numerical solution methods of one- particale, one – dimensional time- independentschrodinger equation are presented that allows one to obtain accurate bound state eigen values andeigen functions for an arbitrary potential energy function v(x). these methods included the fem(finite element method), cooly, numerov and others. here we considered the numerov method inmore details...

Free probability provides tools and techniques for studying the spectra of large Hermitian random matrices. These stochastic eigen-analysis techniques have been invaluable in providing insight into the structure of sample covariance matrices. We briefly outline how these techniques can be used to analytically predict the spectrum of large sample covariance matrices. We discuss how these eigen-a...

In this paper we present an efficient algorithm to compute the eigen decomposition of a matrix that is a weighted sum of the self outer products of vectors such as a covariance matrix of data. A well known algorithm to compute the eigen decomposition of such matrices is though the singular value decomposition, which is available only if all the weights are nonnegative. Our proposed algorithm ac...

A noise abatement method using an eigen function in conjunction with optimizer (Genetic Algorithm) under a space-constrain situation is proposed this study concerning high order wave propagation effect. An used to describe acoustical field and shorten the model four-pole transfer matrix form. The system’s estimates Transmission Loss (TL) for silencers by multiplying individual matrices.

We present a new method for unsupervised, fast speaker adaptation that combines the Eigen-MLLR transform approach with discriminative MLLR. We thereby aim to profit both from the performance improvements that are generally provided by a discriminative approach, and from the reliability that Eigen-MLLR has demonstrated in fast adaptation scenarios. We present first evaluation results on the Spok...

This paper describes a method of fingerprint classification using Eigen Block Directional Fingerprints. The method we propose dispenses off with the preprocessing stages such as segmentation, binarisation, thinning etc. We determine the block directional representation of a fingerprint and the location of the core points in a set of template fingerprints which belong to the same class. In the n...