数字信号处理英文教学课件PPT.ppt
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1、1,Chapter7 LTI Discrete-Time Systems in the Transform Domain,Transfer Function ClassificationTypes of Linear-Phase Transfer FunctionsSimple Digital Filters,2,Types of Transfer Functions,The time-domain classification of a digital transfer function based on the length of its impulse response sequence
2、:-Finite impulse response(FIR)transfer function.-Infinite impulse response(IIR)transfer function.,3,Types of Transfer Functions,In the case of digital transfer functions with frequency-selective frequency responses,there are two types of classifications:(1)Classification based on the shape of the ma
3、gnitude function|H(ei)|.(2)Classification based on the form of the phase function().,4,7.1 Transfer Function Classification Based on Magnitude Characteristics,Digital Filters with Ideal Magnitude ResponsesBounded Real Transfer FunctionAllpass Transfer Function,5,7.1.1 Digital Filters with Ideal Magn
4、itude Responses,A digital filter designed to pass signal components of certain frequencies without distortion should have a frequency response equal to 1 at these frequencies,and should have a frequency response equal to 0 at all other frequencies.,6,Digital Filters with Ideal Magnitude Responses,Th
5、e range of frequencies where the frequency response takes the value of 1 is called the passband.The range of frequencies where the frequency response takes the value of 0 is called the stopband.,7,Digital Filters with Ideal Magnitude Responses,Magnitude responses of the four popular types of ideal d
6、igital filters with real impulse response coefficients are shown below:,8,Digital Filters with Ideal Magnitude Responses,The frequencies c,c1,and c2 are called the cutoff frequencies.An ideal filter has a magnitude response equal to 1 in the passband and 0 in the stopband,and has a 0 phase everywher
7、e.,9,Digital Filters with Ideal Magnitude Responses,Earlier in the course we derived the inverse DTFT of the frequency response HLP(ej)of the ideal lowpass filter:hLPn=sincn/n,-n We have also shown that the above impulse response is not absolutely summable,and hence,the corresponding transfer functi
8、on is not BIBO stable.,10,Digital Filters with Ideal Magnitude Responses,Also,hLPn is not causal and is of doubly infinite length.The remaining three ideal filters are also characterized by doubly infinite,noncausal impulse responses and are not absolutely summable.Thus,the ideal filters with the id
9、eal“brick wall”frequency responses cannot be realized with finite dimensional LTI filter.,11,Digital Filters with Ideal Magnitude Responses,To develop stable and realizable transfer functions,the ideal frequency response specifications are relaxed by including a transition band between the passband
10、and the stopband.This permits the magnitude response to decay slowly from its maximum value in the passband to the 0 value in the stopband.,12,Digital Filters with Ideal Magnitude Responses,Moreover,the magnitude response is allowed to vary by a small amount both in the passband and the stopband.,Ty
11、pical magnitude response specifications of a lowpass filter are shown as:,13,7.1.2 Bounded Real Transfer Functions,A causal stable real-coefficient transfer function H(z)is defined as a bounded real(BR)transfer function if:,for all values of w,Let xn and yn denote,respectively,the input and output o
12、f a digital filter characterized by a BR transfer function H(z)with X(ej)and Y(ej)denoting their DTFTs.,14,Bounded Real Transfer Functions,Integrating the above from-to,and applying Parsevals relation we get:,Then the condition implies that:,15,Bounded Real Transfer Functions,Thus,for all finite-ene
13、rgy inputs,the output energy is less than or equal to the input energy.It implies that a digital filter characterized by a BR transfer function can be viewed as a passive structure.,If,then the output energy is equal to the input energy,and such a digital filter is therefore a lossless system.,16,Bo
14、unded Real Transfer Functions,The BR and LBR transfer functions are the keys to the realization of digital filters with low coefficient sensitivity.,A causal stable real-coefficient transfer function H(z)with is thus called a lossless bounded real(LBR)transfer function.,17,Bounded Real Transfer Func
15、tions,Example:Consider the causal stable IIR transfer function:,where K is a real constant.Its square-magnitude function is given by:,18,Bounded Real Transfer Functions,Thus,for 0,(|H(ej)|2)max=K2/(1-)2|=0(|H(ej)|2)min=K2/(1+)2|=On the other hand,for 0,(2cos)max=-2|=(2cos)min=2|=0Here,(|H(ej)|2)max=
16、K2/(1+)2|=(|H(ej)|2)min=K2/(1-)2|=0,19,Bounded Real Transfer Functions,Hence,is a BR function for K(1-),Plots of the magnitude function for=0.5 with values of K chosen to make H(z)a BR function are shown on the next page.,20,Bounded Real Transfer Functions,Lowpass filter,Highpass filter,21,7.1.3 All
17、pass Transfer Function,The magnitude response of allpass system satisfies:|A(ej)|2=1,for all.The H(z)of a simple 1th-order allpass system is:,Where a is real,and.Or a is complex,the H(z)should be:,22,Allpass Transfer Function,one real pole,one complex pole,23,Allpass Transfer Function,Two order allp
18、ass transfer function,ploes:,zeros:,24,Allpass Transfer Function,Generalize,the Mth-order allpass system is:,If we denote polynomial:,So:,25,Allpass Transfer Function,The numerator of a real-coefficient allpass transfer function is said to be the mirror-image polynomial of the denominator,and vice v
19、ersa.,We shall use the notation to denote the mirror-image polynomial of a degree-M polynomial DM(z),i.e.,26,Allpass Transfer Function,The expression,implies that the poles and zeros of a real-coefficient allpass function exhibit mirror-image symmetry in the z-plane.,27,Allpass Transfer Function,To
20、show that|AM(ej)|=1 we observe that:,Therefore:,Hence:,28,Allpass Transfer Function,Properties:A causal stable real-coefficient allpass transfer function is a lossless bounded real(LBR)function or,equivalently,a causal stable allpass filter is a lossless structure.The magnitude function of a stable
21、allpass function A(z)satisfies:,29,Allpass Transfer Function,(3)Let g()denote the group delay function of an allpass filter A(z),i.e.,The unwrapped phase function c()of a stable allpass function is a monotonically decreasing function of w so that g()is everywhere positive in the range 0 w p.,30,Appl
22、ication of allpass system,Any causal stable system can be denoted as:H(z)=Hmin(z)A(z)Where Hmin(z)is a minimum phase-delay system.Use allpass system to help design stable filters.Use allpass system to help design linear phase system.A simple example.(P361,Fig7.7),31,7.2 Transfer Function Classificat
23、ion Based on Phase Characteristic,1、The phase delay will cause the change of signal waveform,32,2、The nonlinearity of system phase delay will cause the signal distortion,Time delay of signal is depended on systemphase characteristic,33,3、If we ignore the phase information,then,34,linear phase requir
24、ement:,4、The linear phase FIR filter design,-group delay,35,7.2 Transfer Function Classification Based on Phase Characteristic,Zero-Phase Transfer FunctionLinear-Phase Transfer FunctionMinimum-Phase and Maximum-Phase Transfer Functions,36,7.2.1 Zero-Phase Transfer Function,One way to avoid any phase
25、 distortions is to make the frequency response of the filter real and nonnegative,to design the filter with a zero phase characteristic.,But for a causal digital filter it is impossible.,37,Zero-Phase Transfer Function,Only for non-real-time processing of real-valued input signals of finite length,t
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