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)( ?jeG of a digital filter is a periodic function of ? ,and the magnitude response of a realcoefficient digital filter is an even function of ? . As a result, the digital filter specifications are given only for the range ????0 . Digital filter specifications are often given in terms of the loss function, )(lo g20)( 10 ??? jeG?? , in dB. Here the peak passband ripple p? and the minimum stopband attenuation s? are given in dB,., the loss specifications of a digital filter are given by dBpp )1(lo g20 10 ?? ??? , dBss )(log20 10 ?? ?? . Preliminary Considerations As in the case of an analog lowpass filter, the specifications for a digital lowpass filter may alternatively be given in terms of its magnitude response, as in Figure . Here the maximum value of the magnitude in the passband is assumed to be unity, and the maximum passband deviation, denoted as 1/ 21 ?? ,is given by the minimum value of the magnitude in the passband. The maximum stopband magnitude is denoted by 1/A. For the normalized specification, the maximum value of the gain function or the minimum value of the loss function is therefore 0 dB. The quantity max? given by dB)1(lo g20 210m a x ?? ?? Is called the maximum passband attenuation. For p? ?? 1, as is typically the case, it can be shown that pp ??? 2)21(lo g20 10m a x ???? The passband and stopband edge frequencies, in most applications, are specified in Hz, along with the sampling rate of the digital filter. Since all filter design techniques are developed in terms of normalized angular frequencies p? and s? ,the sepcified critical frequencies need to be normalized before a specific filter design algorithm can be applied. Let TF denote the sampling frequency in Hz, and FP and Fs denote, respectively,the passband and stopband edge frequencies in Hz. Then the normalized angular edge frequencies in radians are given by TFFFF pT pTpp ??? 22 ???? TFFFF sT sTss ??? 22 ???? Selection of the Filter Type The second issue of interest is the selection of the digital filter type,.,whether an IIR or an FIR digital filter is to be employed. The objective of digital filter design is to develop a causal transfer function H(z) meeting the frequency response specifications. For IIR digital filter design, the IIR transfer function is a real rational function of 1?z . H(z)=NMdNzzdzdd pMzzpzpp ?????????? ???? ......2211022110 Moreover, H(z) must be a stable transfer function, and for reduced putational plexity, it must be of lowest order N. On the other hand, for FIR filter design, the FIR transfer function is a polynomial in 1?z : ???? NnnznhzH0 ][)( For reduced putational plexity, the degree N of H(z) must be as small as possible. In addition, if a linear phase is desired, then the FIR filter coefficients must satisfy the constraint: ][][ Nnhnh ??? T here are several advantages in using an FIR filter, since it can be designed with exact linear phase and the filter structure is always stable with quantized filter coefficients. However, in most cases, the order NFIR of an FIR filter is considerably higher than the order NIIR of an equivalent IIR filter meeting the same magnitude specifications. In general, the implementation of the FIR filter requires approximately NFIR multiplications per output sample, whereas the IIR filter requires 2NIIR +1 multiplications per output sample. In the former case, if the FIR filter is designed with a linear phase, then the number of multiplications per output sample reduces to approximately (NFIR+1)/2. Likewise, most IIR filter designs result in transfer functions with zeros on the unit circle, and the cascade realization of an IIR filter of order IIRN with all of the zeros on the unit circle requires [(3 IIRN +3)/2] multiplications per output sample. It has been shown that for most practical filter specifications, the ratio NFIR/NIIR is typically of the order of tens or more and, as a result, the IIR filter usually is putationally more efficient[Rab75]. However ,if the group delay of the IIR filter is equalized by cascading it with an allpass equalizer, then the savings in putation may no longer be that significant [Rab75]. In many applications, the linearity of the phase response of the digital filter is not an issue,making the IIR filter preferable because of the lower putational requirements. Basic Approaches to Digital Filter Design In the case of IIR filter design, the most mon practice is to convert the digital filter specifications into analog lowpass prototype filter specifications, and then to transform it into the desired digital filter transfer function G(z). This approach has been widely used for many reasons: (a) Analog approximation techniques are highly advanced. (b) They usually yield closedform solutions. (c) Extensive ta