NDLI: Simulation of brain learning process through a novel fuzzy hardware approach

Content Provider	IEEE Xplore Digital Library
Author	Shouraki, S.B. Honda, N.
Copyright Year	1999
Description	Author affiliation: Dept. of Commun. & Syst., Univ. of Electro-Commun., Tokyo, Japan (Shouraki, S.B.)
Abstract	The problem of understanding and simulating human learning and inferencing procedures is faced from a hardware point of view. A fuzzy modeling method called active learning (ALM) has been developed by the authors. ALM is an adaptive recursive algorithm which tries to express a multi-input multi-output system as a fuzzy combination of some single-input single-output systems. It uses a fuzzy curve fitting technique for behavior extraction or finding the input-output transformation of each of the single-input single-output systems. The mentioned curve fitting technique is called ink drop spread (IDS) which also serves as processing engine for the fuzzy rule of composition. In this paper first we try to develop a digital hardware for executing the IDS. Then, we show that the natural difference between the fuzzy calculating procedure of IDS and the precise nature of digital hardware appears as a serious problem for achieving very high processing speed comparable to that of the brain. As the next step in the hardware development procedure an analog merged digital hardware approach is introduced. It is shown that when preserving the necessary calculating resolution for ALM, the analog merged digital approach reduces the number of circuit elements and increases the processing speed by at least two orders of magnitude. Then it is discussed how a non-precise version of the technology for binary-multi valued-analog-merged operations called Neuron-MOSFET (neuMOS) may suit the non-precise calculating nature of IDS, which appears very promising for achieving the speed of brain learning process. Finally based on the advantages in circuit integration scale and hardware speed obtained through utilizing the binary-multi valued-analog-merged operations for the hardware implementation of IDS a primary concept for a new generation of artificial neural networks structure is developed.
Starting Page	16
Ending Page	21
File Size	495565
Page Count	6
File Format	PDF
ISBN	0780357310
ISSN	1062922X
DOI	10.1109/ICSMC.1999.823126
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-10-12
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain modeling Intrusion detection Fuzzy systems Curve fitting Circuits Neural network hardware Humans Face Inference algorithms Ink
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in