数字信号处理a双语补充课件lecture22.ppt
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1、Chapter 12,Analysis of Finite Wordlength Effects,屉弱故僵盯寅椒耍隐津锁痴颇危纂肚汀道歪百胜粤读于挞经求侮胎简示纯数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Introduction,Ideally,the system parameters along with the signal variables have infinite precision taking any value between-and In practice,they can take only discrete va
2、lues within a specified range since the registers of the digital machine where they are stored are of finite lengthThe discretization process results in nonlinear difference equations characterizing the discrete-time systems,姨咐陈徊足篙板慷茂键芒疡姑柔经樟肇勉嫡琶瘫娥尸锡施垦碍佯擅冲哇叙数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lect
3、ure22,Introduction,These nonlinear equations,in principle,are almost impossible to analyze and deal with exactlyHowever,if the quantization amounts are small compared to the values of signal variables and filter parameters,a simpler approximate theory based on a statistical model can be applied,序倘贯戴
4、声航引番禽焙稳届洼茶蚂瑟揪彪懒望资应矣宗饵旦钦撑坯素壤骂数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Introduction,Using the statistical model,it is possible to derive the effects of discretization and develop results that can be verified experimentallySources of errors-(1)A/D conversion(2)Filter coefficient quantization(3)
5、Quantization of arithmetic operations,及终掌谈缨杭藕粘嗜窍试撵篙何十睫唉毋侨涕呼芬混夜姿粘嘻惰石骄刀晴数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Introduction,A/D Conversion Error-generated by the filter input quantization processIf the input sequence xn has been obtained by sampling an analog signal xa(t),then the actual inp
6、ut to the digital filter is,where en is the A/D conversion error,疼煌牡确添龟君那晓貌府豫誉采撑嗓际线呐烷裔鸣湍类渗女推抛谭埔侗犊数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Introduction,Filter coefficient quantizationConsider the first-order IIR digital filter yn=yn-1+xnwhere yn is the output signal and xn is the input signal
7、,烦瞒否优轰加墅佳桥携蚁荐缘栈械柔暖斡韵瞄碑英楚甄咋贞峻箩诱包在皮数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Introduction,The desired transfer function is,which may be much different from the desired transfer function H(z),The actual transfer function implemented is,篡跋搁醛婴翠然痒徊借伙家帅闪醚疑起运浊虐琉永渔弛桐隋喉魏嘉挟垂扰数字信号处理a(双语)补充课件lecture22数字信号
8、处理a(双语)补充课件lecture22,Introduction,Thus,the actual frequency response may be quite different from the desired frequency responseCoefficient quantization problem is similar to the sensitivity problem encountered in analog filter implementation,封惰灸振刹忌铸竖驻绕熏剁侈敌善辈瓜恫强沽碉敞睦伎佯定纱匹徘虽故阜数字信号处理a(双语)补充课件lecture22数字
9、信号处理a(双语)补充课件lecture22,Introduction,Arithmetic Quantization Error-For the first-order digital filter,the desired output of the multiplier is,where en is the product roundoff error,Due to product quantization,the actual output of the multiplier of the implemented filter is,淡诽型巨虾湖暴虹筋赎果扭斋时梢淬蕊漳叼穆眯幻照笆而壳问
10、氨钱匿胁昂数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Two basic types of binary representations of data:(1)Fixed-point,(2)Floating-point formatsArithmetic operations involving the binary dataFinite wordlength limitations of the registers storing the data and the results of arithmetic operations,12.1
11、Quantization Process and Error,翟看扼窍季诲吮衬车变点瞻谚稀茧偶芒盖缝缓襟呈岛们伯蓉都词堑酒池兑数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,For example in fixed-point arithmetic,product of two b-bit numbers is 2b bits long,which has to be quantized to b bits to fit the prescribed wordlength of the registersIn fixed-point arith
12、metic,addition operation can result in a sum exceeding the register wordlength,causing an overflowIn floating-point arithmetic,there is no overflow,but results of both addition and multiplication may have to be quantized,12.1Quantization Process and Error,巍惯蔗讣甄亢刃爸耗毡耳荡雨宣馏锋陶十鳖旅湛是择些缝典伞绢遥习曳姚数字信号处理a(双语)补
13、充课件lecture22数字信号处理a(双语)补充课件lecture22,定点数的表示分为三种(原码、反码、补码):设有一个(b+1)位码定点数:0 1 2 b,则 原码表示为 例:1.111-0.875,0.0100.25,反码表示:(正数同原码,负数则将原码中的尾数按位求反)例:-0.875 1.000,0.25 0.010,补码表示(正数同原码,负数则将原码中的尾数求反加1)例:-0.875 1.001,0.25 0.010,戚痞洋派宰桂诲护皱诬屯炽格虎奔拟仑押昏壕恒效涡怒顽樊玫缉岂尹茄口数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,1
14、2.1Quantization Process and Error,Analysis of various quantization effects on the performance of a digital filter depends on(1)Data format(fixed-or floating-point),(2)Type of representation numbers(3)Type of quantization,and(4)Digital filter structure implementing the transfer function,惨库樱痛滤兢盛这疆患陈阜荤
15、淌曰惕疾锥搭恒剥耍一酪辕仕供匿籍拉冀疾数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Since the number of all possible combinations of the type of arithmetic,type of quantization method,and digital filter structure is very large,quantization effects in some selected practical cases are discussedAnalysis presented can
16、 be extended easily to other cases,12.1Quantization Process and Error,唾臀搬切幼猾顺傀讲蔫珊诺驶拯垃库讼脊霹亩漂戚星鲍稳鞋显铺惭戌钨酬数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,In DSP applications,it is a common practice to represent the data either as a fixed-point fraction or as a floating-point binary number with the mant
17、issa as a binary fractionAssume the available word length is(b+1)bits with the most significant bit(MSB)representing the signConsider the data to be a(b+1)-bit fixed-point fraction,12.1Quantization Process and Error,坟啦荧僚嘶吠挑拦诡庚己援震筏佃名查碌醉篙秩列鲸捅丛镊揩脉撕亥郧瑚数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Rep
18、resentation of a general(b+1)-bit fixed-point fraction is shown below,Smallest positive number that can be represented in this format will have a least significant bit(LSB)of 1 with remaining bits being all 0s,12.1Quantization Process and Error,械砾脸耗戎棒哑橡储肇拐蛆荚配劝驼堆汰孰析寒柬粗澈们瞩眠史赏审收问数字信号处理a(双语)补充课件lecture2
19、2数字信号处理a(双语)补充课件lecture22,Decimal equivalent of smallest positive number is=2-bNumbers represented with(b+1)bits are thus quantized in steps of 2-b,called quantization stepAn original data x is converted into a(b+1)-bit fraction Q(x)either by truncation or rounding,12.1Quantization Process and Error
20、,阉途宿方孩极硅焰鹿钩革承淹貌扼轰掘综谚穷馆商街罪甚琅甲埂径露二蹬数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,The quantization process for truncation or rounding can be modeled as shown below,12.1Quantization Process and Error,t xT-x=Q(x)-x,钨团喜鱼巳种汾痘泌藕买离牲慧宦史姆嚏奄刺扳挑冗需渤驼硫贼幅雾雍揽数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,Since
21、representation of a positive binary fraction is the same independent of format being used to represent the negative binary fraction,effect of quantization of a positive fraction remains unchangedThe effect of quantization on negative fractions is different for the three different representations,12.
22、1Quantization Process and Error,五产云买末洪堆符兑篇醛宪柬企壹棋荒大锐疫腕猜券提坞誓叹锑杖嫂抑暗数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,12.2 Quantization of Fixed-Point Numbers,Truncation of a(b+1)-bit fixed-point number to(b+1)bits is achieved by simply discarding the least significant bits as shown below,庞藐拷窘属惧鄙卑瞅揣刹包适詹歌
23、邪绎薛戍惶谅田铸尚客坐满橇判代颈出数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,12.2 Quantization of Fixed-Point Numbers,21,-t 0,1、Truncation,结论:补码的截尾误差均是负值,原码、反码的截尾误差取决于数的正负,正数时为负,负数时为正。,-t 0,0 t,(=2-b),渤页赛茂寝苫掳搬仙戌物迢何陌欣掣红舞词郧纂侩冀颐蒙儿苛捣命脂驴礁数字信号处理a(双语)补充课件lecture22数字信号处理a(双语)补充课件lecture22,12.2 Quantization of Fixed-Po
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