基于雙橢圓模型的穩(wěn)定IIR數(shù)字濾波器設(shè)計(jì)算法研究
發(fā)布時(shí)間:2018-02-26 14:21
本文關(guān)鍵詞: IIR數(shù)字濾波器 穩(wěn)定三角形約束 SMSOF方法 雙橢圓模型 改進(jìn)后的雙橢圓模型 MINIMAX設(shè)計(jì) 出處:《杭州電子科技大學(xué)》2015年碩士論文 論文類型:學(xué)位論文
【摘要】:IIR數(shù)字濾波器設(shè)計(jì)有三大挑戰(zhàn):非線性相位,設(shè)計(jì)模型的非凸性,穩(wěn)定性約束。本文主要對(duì)濾波器設(shè)計(jì)模型的非凸性和非線性相位進(jìn)行研究,并給出相應(yīng)的解決辦法。文章首先闡述了IIR數(shù)字濾波器的研究意義與研究現(xiàn)狀,并介紹了數(shù)字濾波器設(shè)計(jì)的基本概念。為了解決穩(wěn)定三角形導(dǎo)致的數(shù)字濾波器設(shè)計(jì)模型非凸性問題,文章采用了現(xiàn)有的SMSOF方法,并把它應(yīng)用于IIR數(shù)字濾波器的MINIMAX設(shè)計(jì)。IIR數(shù)字濾波器有非線性相位問題,為了能夠?qū)ο辔徽`差進(jìn)行有效的控制,文章采用了雙橢圓模型。然后本文在對(duì)現(xiàn)有IIR數(shù)字濾波器設(shè)計(jì)方法研究的基礎(chǔ)上,把雙橢圓模型和SMSOF方法結(jié)合形成了基于雙橢圓模型和SMSOF方法的IIR數(shù)字濾波器設(shè)計(jì)方法,由于此方法用穩(wěn)定三角形這個(gè)充要條件來保證濾波器的穩(wěn)定性,所以能得到性能更好的濾波器。最后,文章又對(duì)上述IIR數(shù)字濾波器設(shè)計(jì)中的雙橢圓模型進(jìn)行改進(jìn),大大提高了IIR數(shù)字濾波器設(shè)計(jì)的效率,并在實(shí)例仿真中得到性能更好的濾波器。本文主要研究內(nèi)容如下: 1.介紹了濾波器及其設(shè)計(jì)的基本概念,以及IIR濾波器設(shè)計(jì)的SMSOF方法和雙橢圓模型。穩(wěn)定三角形是用來保證IIR數(shù)字濾波器穩(wěn)定的穩(wěn)定性約束條件,它具有充要性和線性性質(zhì),為了解決把它引入到IIR濾波器的MINIMAX設(shè)計(jì)所帶來的非凸性問題,文章詳細(xì)介紹了SMSOF方法。通過SMSOF方法,可以將數(shù)字IIR數(shù)字濾波器設(shè)計(jì)問題轉(zhuǎn)化成一系列分母為二階的IIR數(shù)字濾波器設(shè)計(jì)子問題從而避免非凸性的增加。然后文章介紹了雙橢圓模型。雙橢圓模型可以對(duì)所設(shè)計(jì)濾波器的幅值誤差和相位誤差分別進(jìn)行控制,在必要的情況下甚至可以以犧牲幅值誤差為代價(jià),來減小相位誤差,可以解決IIR濾波器的非線性相位問題。 2.將1中介紹的SMSOF方法和雙橢圓模型結(jié)合,提出基于雙橢圓模型的穩(wěn)定IIR濾波器minimax設(shè)計(jì)的SMSOF算法。對(duì)現(xiàn)有的IIR數(shù)字濾波器設(shè)計(jì)方法進(jìn)行研究后發(fā)現(xiàn),文獻(xiàn)[1]提出了雙橢圓模型來設(shè)計(jì)IIR數(shù)字濾波器,這可以對(duì)幅值誤差和相位誤差分別進(jìn)行控制,但是文中用來保證數(shù)字濾波器穩(wěn)定性的約束條件是充分的,這就可能把好的解排除在外,,為了解決這個(gè)問題,我們用穩(wěn)定三角形這個(gè)充要條件來代替文獻(xiàn)[1]中的充分條件,利用基于穩(wěn)定三角形的SMSOF方法來進(jìn)行濾波器的設(shè)計(jì),設(shè)計(jì)出性能更好的濾波器。 3.對(duì)現(xiàn)有的雙橢圓模型進(jìn)行改進(jìn),并提出基于改進(jìn)雙橢圓模型的SMSOF算法。雙橢圓模型中對(duì)相位進(jìn)行約束的橢圓表達(dá)式中含有幅值誤差約束上界這個(gè)變量,這會(huì)導(dǎo)致濾波器設(shè)計(jì)的過程更加復(fù)雜,降低濾波器設(shè)計(jì)的效率,為了解決這個(gè)問題,本文對(duì)雙橢圓模型進(jìn)行改進(jìn),用一個(gè)新的橢圓代替雙橢圓模型中對(duì)相位誤差進(jìn)行約束的橢圓,并在改進(jìn)后的雙橢圓模型基礎(chǔ)上進(jìn)行IIR數(shù)字濾波器MINIMAX設(shè)計(jì);诟倪M(jìn)雙橢圓模型的SMSOF方法明顯提高濾波器的設(shè)計(jì)效率,并在給出的實(shí)例中得到性能更好的濾波器。
[Abstract]:The design of IIR digital filter has three major challenges : non - convex and stability constraints of nonlinear phase and design model . The paper introduces the research significance and research situation of IIR digital filter , and introduces the basic concept of digital filter design . In order to solve the non - convex problem of digital filter design based on double elliptic model and SMSOF method , this paper introduces the double elliptic model and SMSOF method . In order to solve the non - convex problem of IIR digital filter , this paper improves the design efficiency of IIR digital filter , and gets better performance filter in the simulation of IIR digital filter . 1 . The basic concepts of the filter and its design are introduced , and the SMSOF method and the double elliptic model of IIR filter design are introduced . The stable triangle is used to guarantee the stability of IIR digital filter . It has the filling property and the linear property . In order to solve the non - convexity caused by the design of IIR digital filter with IIR filter , this paper introduces the double elliptic model . 2 . Combining the SMSOF method introduced in 1 and the double elliptic model , the SMSOF algorithm for the minimax design of a stable IIR filter based on a double elliptic model is proposed . A double elliptic model is proposed to design the IIR digital filter . 3 . The existing double - elliptic model is improved , and the SMSOF algorithm based on the modified double - elliptic model is proposed . In the double - elliptic model , the variable which is bound to the phase error is contained in the elliptic expression of the constraint of the phase . In order to solve the problem , the double - elliptic model is improved , the design of the IIR digital filter is improved by using a new ellipse instead of the double - elliptic model . The design efficiency of the filter is obviously improved by the improved double - elliptic model SMSOF method , and the filter with better performance is obtained in the given example .
【學(xué)位授予單位】:杭州電子科技大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:TN713.7
【參考文獻(xiàn)】
相關(guān)期刊論文 前1條
1 蕭強(qiáng);Chebyshev濾波器設(shè)計(jì)的優(yōu)化[J];華北電力大學(xué)學(xué)報(bào);2003年03期
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