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基于粒子群算法的超宽带接收机设计 被引量:1

A PSO-based design for ultra wideband receiver
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摘要 超宽带(UWB)接收机具有高度非线性,其传统设计方法依赖于经验,十分复杂。提出了一种基于粒子群优化算法的UWB接收机系统级设计方法 PSO-UWB。该方法基于粒子群改进算法Ad-pISPO,根据系统输出信噪比(SNRout)和重要部件参数之间的关系函数,以SNRout最大化为目标进行参数的优化计算。ADS仿真结果证明,PSO-UWB方法的优化结果符合设计要求,具有可行性。 The design of ultra wideband(UWB) receiver is usually a tedious and experienced based work for its high nonlinear- ity. A novel PSO algorithm based systematic design method named PSO-UWB is proposed in this paper. Based on self-adaptive intelligent single particle optimizer (AdpISPO) algorithm, the relation function between the receiver output signal-to-noise ratio (SNR) and the parameters of key components are used for optimization which target for the maximum SNR Simulation results in ADS show that the optimized results of the PSO-UWB meet the design requirements, and it is feasible.
出处 《电子技术应用》 北大核心 2013年第7期106-108,113,共4页 Application of Electronic Technique
基金 广东省自然科学基金项目(S2012010010255 S2011040001460)
关键词 超宽带接收机 粒子群优化算法 ISPO AdpISPO ADS仿真 UWB receiver particle swarm optimization ISPO AdplSPO ADS simulation
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参考文献7

  • 1WONG A W, MCDONAGH D, KATHIRESAN K, et al. A1 V, micropower system - on - chip for vital-sign monitoringin wireless body sensor networks [J]. IEEE InternationalSolid-State Circuits Conference Papers,2008(2): 138-139.
  • 2YUCE M R,CHEE K H, SUNG C M. Wideband commu-nication for implantable and wearable systems[J].IEEE Mi-crowave Theory and Techniques, 2009 (57): 2597 -2604.
  • 3BOGALE T E, VANDENDORPE L,CHALISE B K. Robusttransceiver optimization for downlink coordinated base stationsystems distributed algorithm[C]. Chongqing:IEEE Transac-tions on Signal Processing,2012,60(1):337-350.
  • 4ZHOU J R,HUANG W G, TIAN T, et al. Face recogni-tion using gabor wavelet and self-adaptive intelligent singleparticle optimizerfC].Chongqing:Chinese Conference on Pat-tern Recognition, 2010.
  • 5纪震,周家锐,廖惠连,吴青华.智能单粒子优化算法[J].计算机学报,2010,33(3):556-561. 被引量:61
  • 6SHI Y, EBERHART R C. A modified particle swarm opti-mizer[C].Proc of International Conference on EvolutionaryComputation. Piscataway: IEEE, 1998:69-73.
  • 7RAZAVI B. RF microelectronics[M]. Price Hall, 1998.

二级参考文献14

  • 1Kennedy J, Eberhart R C. Particle swarm optimization// Proceedings of the IEEE International Conference on Neural Networks, 1995:1942-1948.
  • 2Shi Y, Eberhart R C. A modified particle swarm optimizer// Proceedings of the IEEE International Conference on Evolutionary Computation, 1998:69-73.
  • 3Shi Y, Eberhart R C. Fuzzy adaptive particle swarm optimization//Proceedings of the IEEE Congress on Evolutionary Computation. Seoul, Korea, 2001: 1011-106.
  • 4Clerc M. The swarm and the queen: Toward a deterministic and adaptive particle swarm optimization//Proceedings of the Congress on Evolutionary Computation, 1999: 1951-1957.
  • 5Corne D, Dorigo M, Glover F. New Ideas in Optimization. McGraw Hill, 1999:379-387.
  • 6Angeline P J. Using selection to improve particle swarm optimization//Proceedings of the IEEE International Conference on Evolutionary Computation. Anchorage, Alaska, USA, 1998:84-89.
  • 7Angeline P J. Evolutionary optimization versus particle swarm optimization: Philosophy and performance differences//Proceedings of the 7th Annual Conference on Evolutionary Programming. Germany, 1998:601-610.
  • 8Suganthan P N. Particle swarm optimizer with neighborhood topology on particle swarm performance//Proeeedings of the 1999 Congress on Evolutionary Computation, 1999: 1958- 1962.
  • 9Kennedy J. Small worlds and Mega-minds: Effects of neighborhood topology on particle swarm performance//Proceedings of the Congress on Evolutionary Computation, 1999 1931-1938.
  • 10Peram T, Veeramachaneni K, Mohan C K. Fitness-distanceratio based particle swarm optimization//Proeeedings of the Swarm Intelligence Symposium. Indianapolis, Indiana, USA, 2003: 174-181.

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