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

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 the… Expand

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

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

We present a new technique with potential applications to numerous areas in signal processing including data compression, filtering, blind channel equalization, and feature selection and… Expand

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