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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qiuyi Wu Licheng Jiao Xiaoying Pan Yifei Sun |
| Copyright Year | 2008 |
| Description | Author affiliation: Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ. of China, Xidian Univ., Xi'an, China (Qiuyi Wu; Licheng Jiao; Xiaoying Pan; Yifei Sun) |
| Abstract | Based on the concept and principle of quantum computing and immune system, a novel optimization technique, called a quantum-inspired immune memory algorithm is proposed to deal with the problem of the optimization of the switches of the self-structuring antenna. In the algorithm, the proposed memory strategy realizes the information transfer between the courses of evolution. Theoretical analysis proves that quantum-inspired immune memory algorithm converges to the global optimum. The feasibility, efficiency and effectiveness of the proposed algorithm for optimization of self-structuring antenna, whose performance is analyzed by the fast moment method(Mom) are examined. The results show that quantum-inspired immune memory algorithm performs much better than the genetic algorithms in terms of the quality of solution and convergence speed. In addition, parameter analysis demonstrates our algorithm has stable performance and is insensitive to the change of parameters. |
| Starting Page | 513 |
| Ending Page | 516 |
| File Size | 392427 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769533360 |
| DOI | 10.1109/CSSE.2008.1654 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-12 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Laboratories Software algorithms immune clonal algorithm Switches quantum Genetic algorithms Quantum computing optimization Quantum mechanics Information processing Systems engineering education Performance analysis |
| Content Type | Text |
| Resource Type | Article |
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