• Publications
  • Influence
Generalized Rank-Constrained Matrix Approximations
TLDR
We give an explicit solution to the rank-constrained matrix approximation in Frobenius norm, which is a generalization of the classical approximation of an $m\times n$ matrix $A$ by a matrix of rank k at most. Expand
  • 81
  • 9
  • PDF
Computational methods for modelling of nonlinear systems
Preface Contents 1 Overview I Methods of Operator Approximation in System Modelling 2 Nonlinear Operator Approximation with Preassigned Accuracy 2.1 Introduction 2.2 Generic formulation of theExpand
  • 30
  • 1
Towards theory of generic Principal Component Analysis
TLDR
In this paper, we consider a technique called the generic Principal Component Analysis (PCA) which is based on an extension and rigorous justification of the standard PCA. Expand
  • 31
  • 1
  • PDF
Optimal multilinear estimation of a random vector under constraints of causality and limited memory
TLDR
A new technique is provided for random vector estimation from noisy data under the constraints that the estimator is causal and dependent on at most a finite number p of observations. Expand
  • 4
  • 1
Optimal fixed rank transform of the second degree
We present a new technique with potential applications to numerous areas in signal processing including data compression, filtering, blind channel equalization, and feature selection andExpand
  • 24
An optimal filter of the second order
TLDR
We present a new technique allowing us to find an optimal filter in the class of so-called second-order filters that generalizes and improves an optimal linear filter associated with the concept of Wiener filtering. Expand
  • 22
Computational Methods for Modeling of Nonlinear Systems
  • 13
Filtering of infinite sets of stochastic signals: An approach based on interpolation techniques
TLDR
We propose an approach to the filtering of infinite sets of stochastic signals, K"Y and K"X, based on exploiting a signal interpolation idea. Expand
  • 4
  • PDF
Method of recurrent best estimators of second degree for optimal filtering of random signals
TLDR
A new approach to random signal filtering from observed data is proposed. Expand
  • 11
...
1
2
3
4
5
...