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
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