基于粒子群优化的自适应FIR滤波器用于正弦波频率估计

F. B. Elissa, M. Mismar
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引用次数: 3

摘要

提出了一种检测未知源正弦信号频率的频率估计方法。该系统包含一个自适应有限脉冲响应滤波器(FIR),该滤波器利用了几种随机搜索算法之一——粒子群优化算法(PSO)。PSO将通过在单位圆上找到根的频率来最小化总输出功率。伪谱是通过根的频率消除来实现的,并用于估计源信号的频率及其数量。在估计不需要的干扰信号的频率后,系统可以继续抑制这些信号并保持所需信号的强度。
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Adaptive FIR filter for frequency estimation of sinusoids using particle swarm optimization
A new frequency estimation method which detects frequencies of unknown number of source sinusoidal signals is suggested. The system contains an adaptive finite impulse response filter (FIR) which exploits one of a several random search algorithms, particle swarm optimization (PSO). PSO will work on minimizing the overall output power by finding the frequencies of the roots on the unit circle. The pseudo spectrum is achieved by frequency elimination of the roots and is used to estimate the frequency of the source signals along with their number. After estimating the frequencies of the undesired interfering signals, the system can then work on suppressing these signals and maintaining the strength of the desired signals.
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