Associative Memory of a Pulse-Coupled Noisy Neural Network with Delays: The Lighthouse Model

H. Haken
Additional contact information
H. Haken: University of Stuttgart, Institute for Theoretical Physics 1, Center of Synergetics

A chapter in Traffic and Granular Flow ’99, 2000, pp 173-180 from Springer

Abstract: Abstract We start from the basic equations of a pulse-coupled neural network with arbitrary couplings (“synaptic strengths”) between its elements. The axonal pulses are described by means of a phase, whose rotation speed depends on the dendritic inputs (“lighthouse model”). We include the effects of noise by means of fluctuating forces. We also allow for delays between the neurons. The introduction of time-averaged axonal pulse rates ω ℓ allows us to convert the original, highly nonlinear and stochastic equations into rather simple equations for ui that can be solved directly. The solutions can be interpreted as action of an associate memory.

Keywords: Associative Memory; Firing Pattern; Synaptic Strength; Strong Coupling Limit; Fluctuate Force (search for similar items in EconPapers)
Date: 2000
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-59751-0_16

Ordering information: This item can be ordered from
http://www.springer.com/9783642597510

DOI: 10.1007/978-3-642-59751-0_16

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().