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Content Provider | IEEE Xplore Digital Library |
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Author | Long Thanh Ngo |
Copyright Year | 2012 |
Description | Author affiliation: Department of Information Systems, Le Quy Don Technical University, Hanoi, Vietnam (Long Thanh Ngo) |
Abstract | Nowadays, many studies have focused on representation of type-2 fuzzy sets for reducing complexity of computation of operations, especially type-2 fuzzy logic systems. Advances of nVIDIA computing technology allow to deploy of general purpose applications of GPU by parallelizing algorithms. This paper deals with an approach to representation of type-2 fuzzy sets by dividing domain into grid, called grid-based T2FS. Grid-based T2FS is easily to understand and deploy on platform of Graphics Processor Units (GPU) computing and Compute Unified Device Architecture(CUDA) by taking the advantages of computation on matrices. Experiments are implemented in various applications involving join, meet, negation operation and defuzzification. Results on runtime and accuracy are summarised in comparison with CPU computation to show efficiency of the approach. |
Starting Page | 2885 |
Ending Page | 2890 |
File Size | 521700 |
Page Count | 6 |
File Format | |
ISBN | 9781467317139 |
e-ISBN | 9781467317146 |
e-ISBN | 9781467317122 |
DOI | 10.1109/ICSMC.2012.6378231 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-10-14 |
Publisher Place | Korea (South) |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Fuzzy sets Graphics processing units Instruction sets Complexity theory Fuzzy logic Accuracy Approximation methods fuzzy operations Type-2 fuzzy sets GPU computing defuzzification |
Content Type | Text |
Resource Type | Article |
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