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首页> 外文期刊>Antennas and Wireless Propagation Letters, IEEE >DSP Implementation of the Particle Swarm and Genetic Algorithms for Real-Time Design of Thinned Array Antennas
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DSP Implementation of the Particle Swarm and Genetic Algorithms for Real-Time Design of Thinned Array Antennas

机译:稀疏阵列天线实时设计的粒子群和遗传算法的DSP实现

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摘要

Efficient implementation of sophisticated algorithms on digital signal processing (DSP) chips is a key issue in the implementation of software-defined radios. Here, focusing on beamforming and using the average calculation time and hardware usage as the two indicators of efficiency, a performance comparison between two versions of binary particle swarm optimization (PSO) and genetic algorithm, as the two popular evolutionary techniques, is presented. Using our proposed multirun strategy in DSP platforms, we show that modified PSO results in a reduction by 52% and 67% in the hardware utilization and calculation time as compared to genetic algorithm and binary PSO, respectively.
机译:在数字信号处理(DSP)芯片上有效实施复杂算法是实现软件定义无线电的关键问题。在此,着重讨论波束成形,并以平均计算时间和硬件使用率作为效率的两个指标,提出了两种版本的二进制粒子群优化(PSO)和遗传算法(两种流行的进化技术)之间的性能比较。使用我们在DSP平台中提出的多运行策略,我们证明,与遗传算法和二进制PSO相比,改进的PSO分别将硬件利用率和计算时间减少了52%和67%。

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