The aim of this paper is to propose a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to estimate states and parameters of a highly nonlinear Continuous Stirred Tank Bioreactor (CSTR) in noisy environment. The estimated parameters and states obtained by the proposed KFRNN identifier are used to design an ind...

We present a model-based approach to recover the rigid and non-rigid facial motion parameters in video sequences. Our face model is based on anatomically motivated muscle actuator controls to model the articulated non-rigid motion of a human face. The model is capable of generating a variety of facial expressions by using a small number of muscle actuator controls. We estimate rigid and non-rig...

A novel hybrid method for tracking multiple indistinguishable maneuvering targets using a wireless sensor network is introduced in this paper. The problem of tracking the location of targets is formulated as a Maximum Likelihood Estimation. We propose a hybrid optimization method, which consists of an iterative and a heuristic search method, for finding the location of targets simultaneously. T...

Algorithms for the estimation of nonlinear regression parameters are considered. Adaptive population-based search algorithms are proposed and implemented in deriving reliable estimates at a reasonable time with default setting of their controlling parameters. The algorithms are tested on the NIST collection of datasets containing 27 nonlinear regression tasks of various level of difficulty. The...

The present work is aimed at modelling and characterizing viscoelastic materials by means of a time domain technique. A constitutive equation containing internal variables is proposed. The parameter estimation problem is solved in time domain by means of the Levenberg-Marquadt technique. The effectiveness of the time domain estimation is assessed experimentally for three different structres.

A new method for the solution of the generalized complementarily problem is introduced. The method is based on a no smooth equation reformulation of the generalized complementarily problem and on a no smooth Levenberg-Marquardt method for its solution. The method is shown to be globally convergent. Numerical results are also given.

<span lang="EN-US">In this paper, a new method is developed to model the wind speed data that considered as function of seasonal variations. A hybrid artificial neural network (HANN) investigated based on Weibull distribution model. The presented HANN predicts with and chronological characteristics similar real data. design farm was implemented using MATLAB software. suggested has been ap...

In this paper, we consider nonlinear complementarity problem on management equilibrium model (NCP). To solve the problem, we first establish an error bound estimation for the NCP via a new type of residual function. Based on this, the famous Levenberg-Marquardt (L-M) algorithm is employed for obtaining its solution, and we show that the L-M algorithm is quadratically convergent without nondegen...