NDLI: Hardware implementation of GMDH-type artificial neural networks and its use to predict approximate three-dimensional structures of proteins

Content Provider	IEEE Xplore Digital Library
Author	Braga, A.L.S. Arias-Garcia, J. Llanos, C. Dorn, M. Foltran, A. Coelho, L.S.
Copyright Year	2012
Description	Author affiliation: Produtronica Group. Pontifical Catholic University of Parana. Curitiba - PR, Brazil (Coelho, L.S.) \|\| Vera Cruz Sistemas Computacionais. Brasilia - DF, Brazil (Foltran, A.) \|\| Mechanical Engineer Department. University of Brasilia. Brasilia - DF, Brazil (Braga, A.L.S.; Arias-Garcia, J.; Llanos, C.) \|\| Institute of Informatics. Federal University of Rio Grande do Sul. Porto Alegre - RS, Brazil (Dorn, M.)
Abstract	Implementation of artificial neural networks in software on general purpose computer platforms are brought to an advanced level both in terms of performance and accuracy. Nonetheless, neural networks are not so easily applied in embedded systems, specially when the fully retraining of the network is required. This paper shows the results of the implementation of artificial neural networks based on the Group Method of Data Handling (GMDH) in reconfigurable hardware, both in the steps of training and running. A hardware architecture has been developed to be applied as a co-processing unit and an example application has been used to test its functionality. The application has been developed for the prediction of approximate 3-D structures of proteins. A set of experiments have been performed on a PC using the FPGA as a co-processor accessed through sockets over the TCP/IP protocol. The design flow employed demonstrated that it is possible to implement the network in hardware to be easily applied as an accelerator in embedded systems. The experiments show that the proposed implementation is effective in finding good quality solutions for the example problem. This work represents the early results of the novel technique of applying the GMDH algorithms in hardware for solving the problem of protein structures prediction.
Starting Page	1
Ending Page	8
File Size	586005
Page Count	8
File Format	PDF
ISBN	9781467325707
e-ISBN	9781467325721
e-ISBN	9781467325714
DOI	10.1109/ReCoSoC.2012.6322907
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-09
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins Training Neurons Amino acids Hardware Mathematical model Field programmable gate arrays
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

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