For pt. I see ibid., vol. 4 (1993). This paper considers the problems of regulation and tracking
of a dynamical system when the state variables of the dynamical system are not accessible. …

An attempt is made to indicate how practically viable controllers can be designed using
neural networks, based on results in nonlinear control theory. The problem of stabilization of a …

We present a new algorithm for eliminating excess parameters and improving network
generalization after supervised training. The method," Principal Components Pruning (PCP)", is …

This paper discusses the use of multilayer feed forward neural net (cid: 173) works for
predicting a stock's excess return based on its exposure to various technical and fundamental …

The paper is concerned with the identification of an unknown nonlinear dynamical system
when only the inputs and outputs are accessible for measurement. Under certain assumptions …

This paper is concerned with the identification of an unknown nonlinear dynamic system
when only the inputs and outputs are accessible for measurement. Specifically we investigate …

Artificial neural networks is a rapidly developing field of research which concerns the study
of massively parallel structures composed of simple non-linear processors that are …

The paper introduces two new concepts which are found to be effective in the regulation of
unknown dynamical systems around desired points in the state space. The first deals with the …

The problem of learning efficient representation of a high dimensional input by a lower
dimensional space is investigated. It is shown that a recurrent system of interconnected linear …

Many plan sponsors are challenged with a required rate of return for their plan that is higher
than what the current markets are expected to deliver. This article outlines the severity of the …