Open Access
Open access
IEEE Journal of Selected Topics in Quantum Electronics, volume 19, issue 5, pages 1-12

A Leaky Integrate-and-Fire Laser Neuron for Ultrafast Cognitive Computing

Publication typeJournal Article
Publication date2013-09-01
scimago Q1
wos Q1
SJR1.012
CiteScore9.9
Impact factor5.1
ISSN1077260X, 15584542
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Abstract
We propose an original design for a neuron-inspired photonic computational primitive for a large-scale, ultrafast cognitive computing platform. The laser exhibits excitability and behaves analogously to a leaky integrate-and-fire (LIF) neuron. This model is both fast and scalable, operating up to a billion times faster than a biological equivalent and is realizable in a compact, vertical-cavity surface-emitting laser (VCSEL). We show that-under a certain set of conditions-the rate equations governing a laser with an embedded saturable absorber reduces to the behavior of LIF neurons. We simulate the laser using realistic rate equations governing a VCSEL cavity, and show behavior representative of cortical spiking algorithms simulated in small circuits of excitable lasers. Pairing this technology with ultrafast, neural learning algorithms would open up a new domain of processing.
Found 
Found 

Top-30

Journals

5
10
15
20
25
5
10
15
20
25

Publishers

10
20
30
40
50
60
70
80
90
10
20
30
40
50
60
70
80
90
  • We do not take into account publications without a DOI.
  • Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
  • Statistics recalculated weekly.

Are you a researcher?

Create a profile to get free access to personal recommendations for colleagues and new articles.
Metrics
Share
Cite this
GOST | RIS | BibTex | MLA
Found error?