改進(jìn)的變誤差寬度變階數(shù)LMS算法
發(fā)布時(shí)間:2019-04-09 18:07
【摘要】:針對(duì)自適應(yīng)濾波器階數(shù)失配問(wèn)題,提出一種改進(jìn)的變誤差寬度分?jǐn)?shù)階變階數(shù)LMS算法。該算法中誤差寬度函數(shù)參數(shù)選擇不受噪聲先驗(yàn)知識(shí)的限制,并給出參數(shù)選擇的依據(jù)。對(duì)提出的算法分別在高噪聲、低噪聲以及變化的噪聲環(huán)境下進(jìn)行仿真分析,仿真結(jié)果表明,該算法在未知系統(tǒng)噪聲大小或大小變化的噪聲環(huán)境能夠應(yīng)用,并且具有良好的性能,尤其在高噪聲環(huán)境下能夠獲得較快的階數(shù)收斂速度和較小的穩(wěn)態(tài)誤差,因此該算法的應(yīng)用場(chǎng)合更加廣泛。
[Abstract]:To solve the problem of adaptive filter order mismatch, an improved variable error width fractional order variable order LMS algorithm is proposed. In this algorithm, the parameter selection of error width function is not limited by the prior knowledge of noise, and the basis of parameter selection is given. The proposed algorithm is simulated in high noise, low noise and variable noise environment, and the simulation results show that the proposed algorithm can be applied in the noise environment with unknown system noise size or size change, and has good performance, and the simulation results show that the proposed algorithm can be applied in the noise environment with unknown system noise size or change, and the proposed algorithm has good performance. Especially in high noise environment, faster order convergence rate and smaller steady-state error can be obtained, so the application of this algorithm is more extensive.
【作者單位】: 陜西科技大學(xué)電氣與信息工程學(xué)院;陜西科技大學(xué)理學(xué)院;
【基金】:國(guó)家自然科學(xué)基金資助項(xiàng)目(61401261) 陜西省教育廳科研項(xiàng)目(11KJ1015)
【分類(lèi)號(hào)】:TN713
,
本文編號(hào):2455411
[Abstract]:To solve the problem of adaptive filter order mismatch, an improved variable error width fractional order variable order LMS algorithm is proposed. In this algorithm, the parameter selection of error width function is not limited by the prior knowledge of noise, and the basis of parameter selection is given. The proposed algorithm is simulated in high noise, low noise and variable noise environment, and the simulation results show that the proposed algorithm can be applied in the noise environment with unknown system noise size or size change, and has good performance, and the simulation results show that the proposed algorithm can be applied in the noise environment with unknown system noise size or change, and the proposed algorithm has good performance. Especially in high noise environment, faster order convergence rate and smaller steady-state error can be obtained, so the application of this algorithm is more extensive.
【作者單位】: 陜西科技大學(xué)電氣與信息工程學(xué)院;陜西科技大學(xué)理學(xué)院;
【基金】:國(guó)家自然科學(xué)基金資助項(xiàng)目(61401261) 陜西省教育廳科研項(xiàng)目(11KJ1015)
【分類(lèi)號(hào)】:TN713
,
本文編號(hào):2455411
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