Sökning: onr:"swepub:oai:DiVA.org:ltu-63783" >
High-Dimensional Co...
High-Dimensional Computing as a Nanoscalable Paradigm
-
- Rahimi, Abbas (författare)
- Department of Electrical Engineering and Computer Sciences, University of California at Berkeley
-
- Datta, Sohum (författare)
- Department of Electrical Engineering and Computer Sciences, University of California at Berkeley
-
- Kleyko, Denis (författare)
- Luleå tekniska universitet,Datavetenskap
-
visa fler...
-
- Frady, Edward Paxon (författare)
- Helen Wills Neuroscience Institute, University of California at Berkeley
-
- Olshausen, Bruno (författare)
- Helen Wills Neuroscience Institute, University of California at Berkeley
-
- Kanerva, Pentti (författare)
- Helen Wills Neuroscience Institute, University of California at Berkeley
-
- Rabaey, Jan M. (författare)
- Department of Electrical Engineering and Computer Sciences, University of California at Berkeley
-
visa färre...
-
(creator_code:org_t)
- IEEE, 2017
- 2017
- Engelska.
-
Ingår i: IEEE Transactions on Circuits and Systems Part 1. - : IEEE. - 1549-8328 .- 1558-0806. ; 64:9, s. 2508-2521
- Relaterad länk:
-
https://urn.kb.se/re...
-
visa fler...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- We outline a model of computing with high-dimensional (HD) vectors—where the dimensionality is in the thousands. It is built on ideas from traditional (symbolic) computing and artificial neural nets/deep learning, and complements them with ideas from probability theory, statistics, and abstract algebra. Key properties of HD computing include a well-defined set of arithmetic operations on vectors, generality, scalability, robustness, fast learning, and ubiquitous parallel operation, making it possible to develop efficient algorithms for large-scale real-world tasks. We present a 2-D architecture and demonstrate its functionality with examples from text analysis, pattern recognition, and biosignal processing, while achieving high levels of classification accuracy (close to or above conventional machine-learning methods), energy efficiency, and robustness with simple algorithms that learn fast. HD computing is ideally suited for 3-D nanometer circuit technology, vastly increasing circuit density and energy efficiency, and paving a way to systems capable of advanced cognitive tasks.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Alternative computing
- bio-inspired computing
- hyperdimensional computing
- vector symbolic architectures
- in-memory computing
- Dependable Communication and Computation Systems
- Kommunikations- och beräkningssystem
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas