【摘要】：自適應(yīng)濾波算法在實際應(yīng)用中越來越普遍。經(jīng)典的自適應(yīng)濾波算法,如最小均方(Least Mean Square,LMS)算法和仿射投影算法(Affine Projection Algorithm,APA)雖然在多種自適應(yīng)過程中都有優(yōu)秀的表現(xiàn)。但是,當信道為稀疏信道時,這兩種自適應(yīng)算法的收斂速度將會嚴重下降。成比例類的自適應(yīng)算法利用了回聲路徑脈沖響應(yīng)稀疏的結(jié)構(gòu)特性,廣泛應(yīng)用于回聲消除領(lǐng)域。本論文以類仿射投影(AffineProjection Like,APL)算法為核心,針對稀疏系統(tǒng)(聲學(xué)回聲信道系統(tǒng)和網(wǎng)絡(luò)回聲信道系統(tǒng)),通過成比例思想、M估計思想和凸組合思想進行了詳細的分析和研究工作。首先,為了解決APL算法針對稀疏系統(tǒng)時收斂速度緩慢的問題,本論文將成比例的思想引入到了 APL算法。根據(jù)不同的成比例控制因子計算準則,提出了三種成比例APL算法(標準PAPL算法、IPAPL算法、MPAPL算法)。通過實驗仿真驗證了這三種算法相對于APL算法在應(yīng)對稀疏系統(tǒng)時在收斂速度上的優(yōu)越性。其次,為了使算法具備抗沖激能力,本論文將M估計的思想引入成比例APL算法,提出了基于M估計的成比例類仿射投影算法(標準PAPLM算法、IPAPLM算法、MPAPLM算法)。通過實驗仿真驗證了提出的算法在沖激噪聲環(huán)境下依然能夠保持良好的性能。最后,為了解決固定步長算法無法兼顧收斂速度和穩(wěn)態(tài)誤差的問題,本論文將凸組合的思想引入M估計的成比例類仿射投影算法,通過權(quán)值轉(zhuǎn)移策略對凸組合思想進行改良,以IPAPLM算法為例,提出了權(quán)向量轉(zhuǎn)移策略的凸組合M估計成比例類仿射投影(CIPAPLMWT)算法。通過實驗仿真驗證了提出的算法既能具備較快的收斂速度,又能得到較低的穩(wěn)態(tài)誤差。
[Abstract]:Adaptive filtering algorithm is becoming more and more popular in practical applications. Classical adaptive filtering algorithms, such as the least mean square (Least Mean Square,LMS) algorithm and the affine projection algorithm (Affine Projection Algorithm,APA), have excellent performance in many adaptive processes. However, when the channel is sparse, the convergence speed of the two adaptive algorithms will decrease seriously. The proportional adaptive algorithm takes advantage of the sparse structure of echo path impulse response and is widely used in the field of echo cancellation. In this paper, the affine projection (AffineProjection Like,APL) algorithm is taken as the core. For sparse systems (acoustic echo channel system and network echo channel system), the proportional thought is adopted. M estimation and convex combination are analyzed and studied in detail. Firstly, in order to solve the problem of slow convergence rate of APL algorithm for sparse systems, this paper introduces the idea of proportionality to APL algorithm. Three proportional APL algorithms (standard PAPL algorithm, IPAPL algorithm, MPAPL algorithm) are proposed according to different criteria for calculating proportional control factors. The superiority of the three algorithms in the convergence speed of the sparse system is verified by the simulation results compared with the APL algorithm. Secondly, in order to make the algorithm have the ability of shock resistance, this paper introduces the idea of M estimation into proportional APL algorithm, and proposes a proportional class affine projection algorithm based on M estimation (standard PAPLM algorithm, IPAPLM algorithm, MPAPLM algorithm). The experimental results show that the proposed algorithm can maintain good performance in impulse noise environment. Finally, in order to solve the problem that the fixed step size algorithm can not take into account the convergence rate and steady state error, this paper introduces the idea of convex combination into the proportional affine projection algorithm of M estimation, and improves the convex combination idea by weight transfer strategy. Taking the IPAPLM algorithm as an example, a weighted vector transfer strategy based on convex combination M estimator is proposed, which is proportional class affine projection (CIPAPLMWT) algorithm. The experimental results show that the proposed algorithm not only has a fast convergence rate, but also can get a lower steady state error.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN911.7

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本文編號：2427316