The generalized singular value decomposition (GSVD) is one of the essential tools in
numerical linear algebra. This paper proposes a regularization method, combining Tikhonov …

We propose a transformation of real input vectors to output binary vectors by projection
using a binary random matrix with elements {0, 1} and thresholding. We investigate the rate …

We present a new cognitive architecture named Associative-Projective Neural Networks
(APNNs). APNNs have a multi-module, multi-level, and multi-modal design that works with …

Criteria are developed to determine the optimal number of components of a linear model in
solving a discrete ill-posed problem by the methods of truncated singular value …

We analyze the estimation of the angle, scalar product, and the Euclidean distance of real-
valued vectors using binary vectors with controlled sparsity. Transformation is carried out by …

Averaging over matrices in solving discrete ill-posed problems on the basis of random projection
Page 1 CSIT 2017, 05 – 08 September, 2017, Lviv, Ukraine 473 Averaging over matrices in …

This article analytically studies the dependence of components of the error of reconstructing
the true signal on the number of rows of a random projection matrix. It is shown that, with …

In this paper, we apply randomized algorithms to approximate the total least squares (TLS)
solution of the problem A x≈ b in the large-scale discrete ill-posed problems. A …

A brief overview of our work on the solution of DIP is presented. The stable solution of DIP
we obtained, by truncated singular value decomposition and by random projection methods …

How to Prepare a Paper for IWIM 2007 Page 1 A Model Selection Criterion for Solution of
Discrete Ill-Posed Problems Based on the Singular Value Decomposition Elena G. Revunova …