Parameter Estimation of Sigmoid Superpositions: Dynamical System Approach

Parameter Estimation of Sigmoid Superpositions: Dynamical System Approach

Superposition of sigmoid function over a finite time interval is shown to be equivalent to the linear combination of the solutions of a linearly parameterized system of logistic differential equations. Due to the linearity with respect to the parameters of the system, it is possible to design an effective procedure for parameter adjustment. Stability properties of this procedure are analyzed.

Parameter Estimation of Sigmoid Superpositions

Superposition of sigmoid function over a finite time interval is shown to be equivalent to the linear combination of the solutions of a linearly parameterized system of logistic differential equations. Due to the linearity with respect to the parameters of the system, it is possible to design an effective procedure for parameter adjustment. Stability properties of this procedure are analyzed. S...

Parameter Estimation of Loranz Chaotic Dynamic System Using Bees Algorithm

An important problem in nonlinear science is the unknown parameters estimation in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Bees algorithm (BA) is a new member of me...

Multi-Level Dynamical Parameter Estimation: Hypothesis Testing with Dynamical Systems

The practice of dynamical modeling of perception-action behavior has lagged behind the proliferation of the dynamical perspective. Two methodological roadblocks to dynamical modeling are discussed. First, parameter selection is difficult with current tools. Second, it is unclear what role models have in the larger scientific project beyond their use as descriptions or proofs of concept. In this...

Dynamical parameter estimation using realistic photodetection