Orthogonal method for the Identification of Volterra series. It is an extension of Lee-Schetzen method with two major improvments:

1. Reduced identification uncertainty in diagonal kernel points.

2. Possibility to identify each Volterra kernel with an input with different variance.
This feature reduces the identification noise on lower order kernels and improve the "resolution" on higher order kernels.

For reference see:

Simone Orcioni. Improving the approximation ability of Volterra series identified with a cross-correlation method. DOI:10.1007/s11071-014-1631-7. pp.2861-2869. In NONLINEAR DYNAMICS - ISSN:0924-090X vol. 78 (4) 2014.

Project Activity

See All Activity >

Categories

System, Simulation

License

GNU General Public License version 3.0 (GPLv3)

Follow Volterra2.0

Volterra2.0 Web Site

You Might Also Like
Employee monitoring software with screenshots Icon
Employee monitoring software with screenshots

Clear visibility and insights into how employees work. Even remotely

Our computer monitoring software allows employees, field contractors, and freelancers to manually clock in when they begin working on an assignment. The application will take screenshots randomly or at set intervals, which allows employers to observe the work process. The application only tracks activity when the employee is clocked in. No spying, only transparency.
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Volterra2.0!

Additional Project Details

Intended Audience

Science/Research, Engineering

User Interface

Command-line

Programming Language

MATLAB

Related Categories

MATLAB System Software, MATLAB Simulation Software

Registered

2014-06-03