NeSS: a Simulation Environment for Behavioral Design of Neural Networks for Prediction and Control

Article type: Research Article

Authors: Alippi, Cesare^{a; *} | Casamatta, Fabio^b | Furlan, Leonardo^b | Pelagotti, Andrea^b | Piuri, Vincenzo^b

Affiliations: [a] CNR-CESTIA c/o Department of Electronics and Information, Politecnico di Milano, piazza L. da Vinci 32, 20133 Milano, Italy | [b] Department of Electronics and Information - Politecnico di Milano, piazza L. da Vinci 32, 20133 Milano, Italy

Correspondence: [*] Correspondence to: Dr. Cesare Alippi.

Abstract: The NeSS (Neural Systems Simulator) environment is presented in this paper: it is a exible software package which has been developed to support, analyze and model dynamic non-linear systems for prediction, system identification and control applications, by providing both classical and innovative approaches within a exible and high-level framework. The behavior of each system is easily defined in a graphic way by interconnecting parametrized atomic objects (e.g., algebraic functions and neural networks), whose behaviors can be either predefined or identified by means of a learning procedure. Neural networks play a relevant role in NeSS: rich and easily expandable libraries are given which support different neural structures and learning algorithms.

DOI: 10.3233/ICA-1999-6304

Journal: Integrated Computer-Aided Engineering, vol. 6, no. 3, pp. 223-232, 1999