DocumentCode :
2089189
Title :
Computational neurobiology meets semiconductor engineering
Author :
Hammerstrom, Dan
Author_Institution :
Dept. of Electr. & Comput. Eng., Oregon Graduate Inst., Beaverton, OR, USA
fYear :
2000
fDate :
2000
Firstpage :
3
Lastpage :
12
Abstract :
Many believe that the most important result to come out of the last ten years of neural network research is the significant change in perspective in the neuroscience community towards theory of computational neurobiology and functional neuro-models. Arriving on a fast moving train from the other direction is semiconductor technology, one of the greatest technology success stories of all time transistors are now approaching deep submicron (less than 100 nanometers) in size, and we will soon be building silicon chips with over 1 billion transistors. The marriage of these two technologies is creating what Andy Grove (ex-CEO of Intel) refers to as a strategic inflection point. Although previous attempts at merging these technologies were premature, silicon and computational neurobiology are now merging to create an extremely powerful, and radically new form of computation
Keywords :
neural nets; technological forecasting; computational neurobiology; neural network; neuro-models; semiconductor technology; Biology computing; Biomedical signal processing; Character recognition; Computer networks; Digital signal processing; Hidden Markov models; Intelligent robots; Signal processing algorithms; Silicon; Target recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multiple-Valued Logic, 2000. (ISMVL 2000) Proceedings. 30th IEEE International Symposium on
Conference_Location :
Portland, OR
ISSN :
0195-623X
Print_ISBN :
0-7695-0692-5
Type :
conf
DOI :
10.1109/ISMVL.2000.848593
Filename :
848593
Link To Document :
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