Linear stochastic control: An extended separation principle

Separation principle for linear quadratic control in statistically uncertain stochastic hybrid system∗

We consider the minimax control problem for linear stochastic dynamic system with both continuous and discrete observations. It is assumed that the intensities of the continuousand discrete-time noises are not known exactly. The only information available is that the noise intensities are constant and belong to a priori known compact uncertainty sets. The minimax control equations are provided ...

The Separation Principle in Linear Regression

text may be freely shared among individuals, but it may not be republished in any medium without express written consent from the authors and advance notiication of the editor. Abstract In linear regression problems in which an independent variable is a total of two or more characteristics of interest, it may be possible to improve the t of a regression equation substantially by regressing agai...

An extended variational principle

Blind Signal Separation Using an Extended Infomax Algorithm

The Infomax algorithm is a popular method in blind source separation problem. In this article an extension of the Infomax algorithm is proposed that is able to separate mixed signals with any sub- or super-Gaussian distributions. This ability is the results of using two different nonlinear functions and new coefficients in the learning rule. In this paper we show how we can use the distribution...

Blind Signal Separation Using an Extended Infomax Algorithm

The Infomax algorithm is a popular method in blind source separation problem. In this article an extension of the Infomax algorithm is proposed that is able to separate mixed signals with any sub- or super-Gaussian distributions. This ability is the results of using two different nonlinear functions and new coefficients in the learning rule. In this paper we show how we can use the distribution...