本文關(guān)鍵詞：數(shù)字助聽器中自適應(yīng)回波抵消算法的研究　出處：《哈爾濱工業(yè)大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 回波抵消 NLMS 變步長(zhǎng) 分塊更新 遺忘因子

【摘要】：助聽器能幫助聽力障礙患者改善聽力,經(jīng)過數(shù)百年的發(fā)展,助聽器已經(jīng)進(jìn)入到了全數(shù)字時(shí)代。聲音的高質(zhì)量、助聽器的微型化是我們所追求的目標(biāo)。微型化意味著麥克風(fēng)與揚(yáng)聲器的位置很接近,導(dǎo)致聲源經(jīng)過處理輸出,在被人耳接收的同時(shí),還有一部分會(huì)被麥克風(fēng)重新拾取,形成回波。回波被不斷地放大,容易形成嘯叫,造成系統(tǒng)的不穩(wěn)定,也限制了助聽器的最大穩(wěn)定增益,降低了患者的語(yǔ)言可懂度以及聽力舒適度。為了解決助聽器中回波造成的干擾問題,本論文將針對(duì)自適應(yīng)回波抵消算法展開研究。本論文深入了解了傳統(tǒng)的回波抵消算法LMS、RLS以及NLMS算法,這些算法的系數(shù)更新方式是逐點(diǎn)更新,運(yùn)算量較大�？紤]到數(shù)字助聽器對(duì)實(shí)時(shí)性的高要求,引入了分塊算法BLMS,形成NBLMS算法改變?yōu)V波器系數(shù)更新方式,降低算法復(fù)雜度。雖然NBLMS算法解決了由于逐點(diǎn)更新造成的系統(tǒng)資源浪費(fèi)的問題,但是NBLMS算法存在著收斂效果不好、殘留大、音質(zhì)不好等問題。在此基礎(chǔ)上,將當(dāng)前時(shí)刻之前的估計(jì)誤差引入歸一化步長(zhǎng)因子中,提出了NBLMS_S算法;之后在此基礎(chǔ)上設(shè)計(jì)了兩個(gè)改進(jìn)算法。一是利用RLS算法中“遺忘因子”的思想對(duì)濾波器系數(shù)的更新過程做了改進(jìn),生成了NBLMS_MKS算法。另外一個(gè)算法λVS_BLMS也是基于NBLMS_S做的改進(jìn),改變了步長(zhǎng)變化方式,在估計(jì)誤差與變步長(zhǎng)之間搭建一種類似Sigmoid表達(dá)式的非線性關(guān)系。在實(shí)現(xiàn)改進(jìn)算法NBLMS_MKS和λVS_BLMS的設(shè)計(jì)后,將兩者在PC機(jī)上進(jìn)行仿真,并與最初的塊處理算法NBLMS_S做性能對(duì)比。通過性能對(duì)比和運(yùn)算量的分析,發(fā)現(xiàn)相較于NBLMS_S算法,改進(jìn)算法在有更快的收斂速度和更高的收斂精度。并且,在噪聲處理方面,λVS_BLMS有更好的抗噪性,更適合運(yùn)用在微型化的助聽器中,擴(kuò)大了助聽器的適用范圍。
[Abstract]:Hearing aids can help people with hearing impairment to improve their hearing. After hundreds of years of development, hearing aids have entered the digital age. The high quality of sound. Miniaturization of hearing aids is our goal. Miniaturization means that the microphone is close to the speaker, resulting in the sound source being processed and output while being received by the human ear. Others will be picked up by the microphone to form an echo. The echo is constantly amplified, resulting in a screeching, resulting in instability of the system and limiting the maximum stable gain of the hearing aid. The speech intelligibility and hearing comfort of the patients were reduced. In order to solve the interference caused by echo in hearing aid. This paper will focus on adaptive echo cancellation algorithms. In this paper, we deeply understand the traditional echo cancellation algorithm LMS-RLS and NLMS algorithm, these algorithms update the coefficients point by point. Considering the high requirement of real time of digital hearing aid, the block algorithm BLMS is introduced to form the NBLMS algorithm to change the filter coefficient updating method. Reduce the complexity of the algorithm. Although the NBLMS algorithm solves the problem of system resource waste caused by point-by-point update, but the NBLMS algorithm has poor convergence effect and large residual. On the basis of this, the estimation error before the current moment is introduced into the normalized step size factor, and the NBLMS_S algorithm is proposed. Then two improved algorithms are designed. One is to improve the updating process of filter coefficients by using the idea of "forgetting factor" in RLS algorithm. NBLMS_MKS algorithm is generated. Another algorithm 位 VS_BLMS is also based on the improvement made by NBLMS_S, changing the way of step size change. A nonlinear relationship similar to the Sigmoid expression is built between the estimation error and the variable step size. After the design of the improved algorithms NBLMS_MKS and 位 VS_BLMS is implemented. The two algorithms are simulated on PC and compared with the original block processing algorithm (NBLMS_S). Through the performance comparison and computation analysis, it is found that the algorithm is compared with the NBLMS_S algorithm. The improved algorithm has faster convergence speed and higher convergence accuracy. Moreover, 位 VS_BLMS has better noise resistance in noise processing, and is more suitable for use in miniaturized hearing aids. The scope of application of hearing aid is expanded.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TN713

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