DocumentCode :
2896185
Title :
ULSI architectures for artificial neural networks
Author :
Rückert, Ulrich
Author_Institution :
Heinz Nixdorf Inst., Paderborn Univ., Germany
fYear :
2001
fDate :
2001
Firstpage :
436
Lastpage :
442
Abstract :
Three different hardware implementations of artificial neural networks are presented. The chips are model-specific integrated circuits for neural associative memories, self-organizing feature maps and local cluster neural networks. Some of the key implementational issues are considered and especially the question of resource-efficiency is discussed
Keywords :
ULSI; neural nets; self-organising feature maps; ULSI architectures; artificial neural networks; hardware implementations; implementational issues; local cluster neural networks; model-specific integrated circuits; neural associative memories; resource efficiency; self-organizing feature maps; Artificial neural networks; Associative memory; Integrated circuit measurements; Integrated circuit modeling; Integrated circuit technology; Microelectronics; Neural network hardware; Neural networks; Semiconductor device measurement; Ultra large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing, 2001. Proceedings. Ninth Euromicro Workshop on
Conference_Location :
Mantova
Print_ISBN :
0-7695-0987-8
Type :
conf
DOI :
10.1109/EMPDP.2001.905072
Filename :
905072
Link To Document :
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