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A fast convergence algorithm for sparse-tap adaptive FIR filters identifying an unknown number of dispersive regions

机译:用于稀疏抽头自适应FIR滤波器的快速收敛算法,用于识别未知数量的色散区域

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This paper proposes a fast convergence algorithm for sparse-tap adaptive finite impulse response (FIR) filters to identify an unknown number of multiple dispersive regions. Coefficient values and tap-positions of the adaptive filter are simultaneously controlled. A constrained region for new-tap positions is selected from equisize subgroups of all possible tap-positions, and it hops from one subgroup to another to cover multiple dispersive regions. The hopping order and the stay time for each subgroup are adaptively determined based on the absolute coefficient values. Simulation results with colored signals show that the proposed algorithm saves more than 80% in the convergence time over the full-tap NLMS and 50% over the STWQ. Tracking capability of the proposed algorithm exhibits its superior characteristics. These characteristics are confirmed by hardware evaluations with a telephone network simulator.
机译:本文提出了一种用于稀疏抽头自适应有限冲激响应(FIR)滤波器的快速收敛算法,以识别未知数量的多个色散区域。同时控制自适应滤波器的系数值和抽头位置。从所有可能的抽头位置的相等子组中选择一个新抽头位置的受约束区域,它从一个子组跳到另一个子组以覆盖多个分散区域。基于绝对系数值自适应地确定每个子组的跳变顺序和停留时间。彩色信号的仿真结果表明,所提出的算法在全抽头NLMS上节省了80%以上的收敛时间,在STWQ上节省了50%。所提算法的跟踪能力表现出其优越的特性。这些特征通过电话网络模拟器的硬件评估得到确认。

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