Ruhr-Universität Bochum zum Inhalt Startseite der RUB pix
Startseite UniStartseite
Überblick UniÜberblick
A-Z UniA-Z
Suche UniSuche
Kontakt UniKontakt

Das Siegel
Naturwissenschaften Ingenieurwissenschaften Geisteswissenschaften Medizinische Einrichtungen Zentrale Einrichtungen
pix Lehrstuhl Mathematik & Informatik
Complexity of Boolean Computations for a Spiking Neuron
Unser Angebot: Mitarbeiter | Forschung | Lehre   
Startseite » Mitarbeiter » M. Schmitt » Complexity of Boolean Computations for a Spiking Neuron

pix pix Complexity of Boolean Computations for a Spiking Neuron
We investigate the computational power of a model for a spiking neuron in the Boolean domain by comparing it with traditional neuron models such as threshold gates (or McCulloch-Pitts neurons) and sigma-pi units (or polynomial threshold gates). In particular, we estimate the number of gates required to simulate a spiking neuron by a disjunction of threshold gates and we establish tight bounds for this threshold number. Furthermore, we analyze the degree of the polynomials that a sigma-pi unit must use when simulating a spiking neuron. We show that this degree cannot be bounded by any fixed value. Our results give evidence that the use of continuous time as a computational resource endows single-cell models with substantially larger computational capabilities.

Zum Seitenanfang  Seitenanfang | Diese Seite drucken
Letzte Änderung: 03.02.2003 | Ansprechpartner: Webmaster