DocumentCode :
2349782
Title :
An FPGA implementation of GENET for solving graph coloring problems
Author :
Lee, T.K. ; Leong, P.H.W. ; Lee, K.H. ; Chan, K.T. ; Hui, S.K. ; Yeung, H.K. ; Lo, M.F. ; Lee, J.H.M.
Author_Institution :
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
fYear :
1998
fDate :
15-17 Apr 1998
Firstpage :
284
Lastpage :
285
Abstract :
Constraint satisfaction problems (CSPs) can be used to model problems in a wide variety of application areas, such as time-table scheduling, bandwidth allocation, and car-sequencing. To solve a CSP means finding appropriate values for its set of variables such that all of the specified constraints are satisfied. Almost all CSPs have exponential time complexity and instances of them may require a prohibitively large amount of time to solve. Consequently, much research has been done in developing efficient methods to solve CSPs. In particular, a generic neural network (GENET) model, developed by C.J. Wang and E.P.K. Tsang (1991), has been demonstrated to work extremely well in solving many CSPs, often finding solutions where other methods fail
Keywords :
constraint handling; field programmable gate arrays; graph colouring; neural net architecture; FPGA implementation; GENET; bandwidth allocation; car-sequencing; constraint satisfaction problems; generic neural network model; graph coloring problems; time complexity; time-table scheduling; Application software; Channel allocation; Computer networks; Computer science; Field programmable gate arrays; Microprogramming; Neural networks; Processor scheduling; Read-write memory; Turning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
FPGAs for Custom Computing Machines, 1998. Proceedings. IEEE Symposium on
Conference_Location :
Napa Valley, CA
Print_ISBN :
0-8186-8900-5
Type :
conf
DOI :
10.1109/FPGA.1998.707918
Filename :
707918
Link To Document :
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