Abstract
We define a new performance parameter, ‘associativity’, which measures the error-correcting capability of the Hopfield network. Simulations show that the associativity of a delta-trained network is inferior to one trained uiing the Hebbian rule, and that a novel combination of the two training strategies yields a performance which is superior to either
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
