Abstract:
This work considers the parameter estimation from measurements of the logistic map. The problem is solved in the context of optimization approach, which assumes minimization of a cost function that measures the difference between the time series obtained from the model equation and measurements. Complex dynamics of the logistic map leads to the multi-extremal optimization problem. It requires using appropriate computational techniques. This work presents the application of particle swarm optimization in searching for the global minimum of the cost function.
Fulltext:
PDF file (466 kB)