Neuronal state feedback learning of Cohen-Grossberg networks

✍ Scribed by Apostolou, N.; King, R. E.

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 113 KB
• Volume: 27
• Category: Article
• ISSN: 0098-9886
• DOI: 10.1002/(sici)1097-007x(199905/06)27:3<331::aid-cta50>3.0.co;2-8

✦ Synopsis

This paper proposes a direct synaptic weight training technique for a class of additive dynamic auto-associative neural networks based on the Cohen}Grossberg neuronal activation model. The proposed technique is based on the Jurdjevic}Quinn stabilization method for control a$ne systems. Asymptotic stability of the training law is guaranteed and regions of attraction around each point attractor are prede"ned. The proposed technique requires the solution of signi"cantly fewer non-linear di!erential equations and is considerably simpler and faster than existing training techniques.