DocumentCode :
1449869
Title :
Neuromorphic Adaptive Plastic Scalable Electronics: Analog Learning Systems
Author :
Srinivasa, Narayan ; Cruz-Albrecht, Jose M.
Author_Institution :
Inf. & Syst. Sci. Dept., HRL Labs., Malibu, CA, USA
Volume :
3
Issue :
1
fYear :
2012
Firstpage :
51
Lastpage :
56
Abstract :
This article provides an overview of the HRL Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) project and progress made thus far. The multifaceted SyNAPSE program seeks to advance the state of the art in biological algorithms and in developing a new generation of neuromorphic electronic machines necessary for the efficient implementation of these algorithms by drawing inspiration from biology.The fundamental premise of the HRL team to develop brain architecture and related tools has been to recognize that there was a sequence of evolutionary events by which the brain architecture evolved from a primitive brain into a modern brain.
Keywords :
biomedical electronics; brain; neurophysiology; SyNAPSE; biological algorithms; brain architecture; evolutionary events; neuromorphic adaptive plastic scalable electronics; Adaptive systems; Artificial intelligence; Biological system modeling; Complexity theory; Intelligent systems; Neuromorphics; Programmable control; Research and development; Animals; Humans; Neural Networks (Computer); Software; Transfer (Psychology);
fLanguage :
English
Journal_Title :
Pulse, IEEE
Publisher :
ieee
ISSN :
2154-2287
Type :
jour
DOI :
10.1109/MPUL.2011.2175639
Filename :
6153093
Link To Document :
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