An exponential-decay synapse integrated circuit for bio-inspired neural networks

Authors:
Ludovic Alvado;Sylvain Saïghi;Jean Tomas;Sylvie Renaud
Affiliations:
Laboratoire IXL, CNRS UMR, ENSEIRB-Université Bordeaux, Talence, France;Laboratoire IXL, CNRS UMR, ENSEIRB-Université Bordeaux, Talence, France;Laboratoire IXL, CNRS UMR, ENSEIRB-Université Bordeaux, Talence, France;Laboratoire IXL, CNRS UMR, ENSEIRB-Université Bordeaux, Talence, France
Venue:
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Year:
2003

Citing 7
Cited 1

Products of automata

Products of automata
Brains, machines, and mathematics (2nd ed.)

Brains, machines, and mathematics (2nd ed.)
Computing with membranes

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Membrane Computing: An Introduction

Membrane Computing: An Introduction
Multiset Automata

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Gamma and the Chemical Reaction Model: Fifteen Years After

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Tissue P systems

Theoretical Computer Science

Automated parameter estimation of the hodgkin-huxley model using the differential evolution algorithm: Application to neuromimetic analog integrated circuits

Neural Computation

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Abstract

We present in this paper a neural-like membrane system solving the SAT problem in linear time. These neural Psystems are nets of cells working with multisets. Each cell has a finite state memory, processes multisets of symbol-impulses, and can send impulses ("excitations") to the neighboring cells. The maximal mode of rules application and the replicative mode of communication between cells are at the core of the efficiency of these systems.