CINTIA: a neuro-fuzzy real time controller for low power embedded systems
- 1 January 1995
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
This paper describes CINTIA, a neuro-fuzzy real-time controller based on pulse stream computation techniques and designed for applications in low power embedded systems. The proposed system mixes two different approaches, namely neuro-fuzzy controllers and finite state automata. The former are implemented by means of a custom neural chip (manufactured by ES2), while the latter are implemented as sequential code on a traditional microcontroller. The proposed system is used to demonstrate the advantages of mixing the two approaches and the feasibility of embedded neuro-fuzzy control systems. A low power single chip version is also under desigKeywords
This publication has 7 references indexed in Scilit:
- An analog processor architecture for a neural network classifierIEEE Micro, 1994
- A comparison between analog and pulse stream VLSI hardware for neural networks and fuzzy systemsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1994
- USING COHERENT PULSE WIDTH AND EDGE MODULATIONS IN ARTIFICIAL NEURAL SYSTEMSInternational Journal of Neural Systems, 1993
- Integrated pulse stream neural networks: results, issues, and pointersIEEE Transactions on Neural Networks, 1992
- Pulse-stream VLSI neural networks mixing analog and digital techniquesIEEE Transactions on Neural Networks, 1991
- The truck backer-upper: an example of self-learning in neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1989
- Introduction to neural networks for intelligent controlIEEE Control Systems Magazine, 1988