DocumentCode :
3293599
Title :
UB1 - a recurrent neural network based parallel machine for solving simultaneous linear equations
Author :
Hang, D.L. ; Arsgao, A. ; Silva, Jorge L. ; Marques, Eduardo ; Hillesland, Karl
Author_Institution :
Dept. of Electr. & Comput. Eng., Washington State Univ., Pullman, WA, USA
fYear :
1997
fDate :
3-5 Dec 1997
Firstpage :
14
Lastpage :
18
Abstract :
This paper describe the electronic realization of a recently proposed recurrent neural network for solving simultaneous linear equations which can be found in many mathematical model formulations. In many large-scale problems, the number of unknowns involved is very large. These large-scale problems often need to be solved in real-time. In this study, a systolic array is proposed that provides linear speedup over sequential execution on a single processor machine. The systolic array is based on a ring topology and synchronous execution, allowing for the use of a single controller for all processing elements. The architecture proposed has been implemented on field programmable gate arrays and verified. Issue such as architecture design and implementation are discussed, and initial testing results are also included
Keywords :
field programmable gate arrays; linear algebra; mathematics computing; network topology; neural chips; neural net architecture; parallel machines; recurrent neural nets; systolic arrays; UB1 recurrent neural network; field programmable gate arrays; neural net architecture; parallel machine; real-time systems; ring topology; simultaneous linear equation solving; synchronous execution; systolic array; Equations; Field programmable gate arrays; Large-scale systems; Mathematical model; Parallel machines; Process control; Recurrent neural networks; Systolic arrays; Testing; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1997. Proceedings., IVth Brazilian Symposium on
Conference_Location :
Goiania
Print_ISBN :
0-8186-8070-9
Type :
conf
DOI :
10.1109/SBRN.1997.645852
Filename :
645852
Link To Document :
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