-
Notifications
You must be signed in to change notification settings - Fork 5
Multiple-variance Volterra series Identification Tool
License
orcioni/Volterra2.0
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
New files added to the Volterra-Wiener tool: ident_volt.m :Identification of Wiener system with algorithm proposed in [1] Simone Orcioni, Massimiliano Pirani, and Claudio Turchetti. Advances in Lee-Schetzen method for Volterra filter identification. Multidimensional Systems and Signal Processing, 16(3):265-284, 2005. ident_volt_20.m :Identification of Wiener system with the mukltiple-variance algorithm proposed in [2] Simone Orcioni. Improving the approximation ability of Volterra series identified with a cross-correlation method. Nonlinear Dynamics, 2014. Wiener2Volterra_20.m : Formulas for Wiener to Volterra conversion for mukltiple-variance algorithm. In the directory examples you can find the code used in [2] to obtain all published results. The multiple variance algorithm has been updated to use the computational complexity reduction method presented in [3] Orcioni, S., Terenzi, A., Cecchi, S., Piazza, F., & Carini, A. (2018). Identification of Volterra Models of Tube Audio Devices using Multiple-Variance Method. Journal of the Audio Engineering Society, 66(10), 823–838. https://doi.org/10.17743/jaes.2018.0046
About
Multiple-variance Volterra series Identification Tool
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published