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Problems 379 Plot the impulse response and the magnitude response (in dB) of the designed filter. Do not use the fir1 function. P7.11 Design a bandpass filter using the Hamming window design technique. The specifications are lower stopband edge: 0.3π As =50dB upper stopband edge: 0.6π lower passband edge: 0.4π upper passband edge: 0.5π R p =0.5 dB Plot the impulse response and the magnitude response (in dB) of the designed filter. Do not use the fir1 function. P7.12 Design a highpass filter using one of the fixed window functions. The specifications are stopband edge: 0.4π, A s =50dB passband edge: 0.6π, R p =0.004 dB Plot the zoomed magnitude response (in dB) of the designed filter in the passband to verify the passband ripple R p.Donot use the fir1 function. P7.13 Using the Kaiser window method, design a linear-phase FIR digital filter that meets the following specifications 0.975 ≤|H(e jω )|≤1.025, 0 ≤ ω ≤ 0.25π 0 ≤|H(e jω )|≤0.005, 0.35π ≤ ω ≤ 0.65π 0.975 ≤|H(e jω )|≤1.025, 0.75π ≤ ω ≤ π Determine the minimum length impulse response h(n) ofsuch a filter. Provide a plot containing subplots of the amplitude response and the magnitude response in dB. Do not use the fir1 function. P7.14 We wish to use the Kaiser window method to design a linear-phase FIR digital filter that meets the following specifications: 0 ≤|H(e jω )|≤0.01, 0 ≤ ω ≤ 0.25π 0.95 ≤|H(e jω )|≤1.05, 0.35π ≤ ω ≤ 0.65π 0 ≤|H(e jω )|≤0.01, 0.75π ≤ ω ≤ π Determine the minimum length impulse response h(n) ofsuch a filter. Provide a plot containing subplots of the amplitude response and the magnitude response in dB. Do not use the fir1 function. P7.15 Design the staircase filter of Example 7.26 using the Kaiser window approach. The specifications are Band-1: 0 ≤ ω ≤ 0.3π, Ideal gain = 1, δ 1 =0.01 Band-2: 0.4π ≤ ω ≤ 0.7π, Ideal gain = 0.5, δ 2 =0.005 Band-3: 0.8π ≤ ω ≤ π, Ideal gain = 0, δ 3 =0.001 Compare the filter length of this design with that of Example 7.26. Provide a plot of the magnitude response in dB. Do not use the fir1 function. Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
380 Chapter 7 FIR FILTER DESIGN P7.16 Design a bandpass filter using a fixed window design technique that has the minimum length and that satisfies the following specifications: } lower stopband edge = 0.3π A upper stopband edge = 0.6π s =40dB } lower passband edge = 0.4π R upper passband edge = 0.5π p =0.5 dB. Provide a plot of the log-magnitude response in dB and stem plot of the impulse response. P7.17 Repeat Problem P7.9 using the fir1 function. P7.18 Repeat Problem P7.10 using the fir1 function. P7.19 Repeat Problem P7.11 using the fir1 function. P7.20 Repeat Problem P7.12 using the fir1 function. P7.21 Repeat Problem P7.13 using the fir1 function. P7.22 Repeat Problem P7.14 using the fir1 function. P7.23 Consider an ideal lowpass filter with the cutoff frequency ω c =0.3π. Wewantto approximate this filter using a frequency sampling design in which we choose 40 samples. 1. Choose the sample at ω c equal to 0.5, and use the naive design method to compute h(n). Determine the minimum stopband attenuation. 2. Now vary the sample at ω c, and determine the optimum value to obtain the largest minimum stopband attenuation. 3. Plot the magnitude responses in dB of the preceding two designs in one plot, and comment on the results. P7.24 Design the bandstop filter of Problem P7.10 using the frequency sampling method. Choose the order of the filter appropriately so that there are two samples in the transition band. Use optimum values for these samples. Compare your results with those obtained using the fir2 function. P7.25 Design the bandpass filter of Problem P7.11 using the frequency sampling method. Choose the order of the filter appropriately so that there are two samples in the transition band. Use optimum values for these samples. Compare your results with those obtained using the fir2 function. P7.26 Design the highpass filter of Problem P7.12 using the frequency sampling method. Choose the order of the filter appropriately so that there are two samples in the transition band. Use optimum values. Compare your results with those obtained using the fir2 function. P7.27 Consider the filter specifications given in Figure P7.1. Use the fir2 function and a Hamming window to design a linear-phase FIR filter via the frequency sampling method. Experiment with the filter length to achieve the required design. Plot the amplitude response of the resulting filter. P7.28 Design a bandpass filter using the frequency sampling method. Choose the order of the filter appropriately so that there is one sample in the transition band. Use optimum value for this sample. The specifications are as follows: lower stopband edge = 0.3π upper stopband edge = 0.7π } A s =40dB Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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Digital Signal Processing Using MAT
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Contents PREFACE xi 1 INTRODUCTION
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CONTENTS vii 6 IMPLEMENTATION OF DI
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CONTENTS ix 11.3 Suppression of Nar
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Preface From the beginning of the 1
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PREFACE xiii implementation. The di
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PREFACE xv ACKNOWLEDGMENTS We are i
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CHAPTER 1 Introduction During the p
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Overview of Digital Signal Processi
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A Brief Introduction to MATLAB 5 It
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A Brief Introduction to MATLAB 7 Va
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A Brief Introduction to MATLAB 9 us
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A Brief Introduction to MATLAB 11 o
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A Brief Introduction to MATLAB 13 o
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A Brief Introduction to MATLAB 15 T
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Applications of Digital Signal Proc
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Applications of Digital Signal Proc
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Brief Overview of the Book 21 In al
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Discrete-time Signals 23 In MATLAB
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Discrete-time Signals 25 For exampl
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Discrete-time Signals 27 n = min(mi
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Discrete-time Signals 29 Solution a
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Discrete-time Signals 31 Sequence i
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Discrete-time Signals 33 The quanti
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Discrete-time Signals 35 Rectangula
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Discrete Systems 37 In DSP we will
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Discrete Systems 39 every input seq
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Convolution 41 2 Input Sequence 1.5
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Convolution 43 x(k) and h(k) x(k) a
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Convolution 45 Hence y(n) ={6, 31,
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Difference Equations 47 Note that t
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Difference Equations 49 Solution Fr
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Difference Equations 51 8 Output Se
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Problems 53 IIR filter If the impul
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Problems 55 1. Modify the evenodd f
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Problems 57 2. x(n) ={1, 1, 0, 1, 1
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CHAPTER 3 The Discrete-time Fourier
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The Discrete-time Fourier Transform
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The Properties of the DTFT 67 TABLE
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The Properties of the DTFT 69 8. Mu
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The Properties of the DTFT 71 60 Ma
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The Properties of the DTFT 73 2 Rea
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The Frequency Domain Representation
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Sampling and Reconstruction of Anal
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Problems 97 % check >> error = max(
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Problems 99 Remember that the above
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Problems 101 P3.16 Foralinear, shif
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CHAPTER 4 The z-Transform In Chapte
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The Bilateral z-Transform 105 Im{z}
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Important Properties of the z-Trans
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Inversion of the z-Transform 113 wh
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Inversion of the z-Transform 115 be
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Inversion of the z-Transform 117 He
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System Representation in the z-Doma
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Solutions of the Difference Equatio
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Problems 135 4. x(n) =n 2 (2/3) n
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Problems 137 2. Using (4.32), deter
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Problems 139 It is also known that
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CHAPTER 5 The Discrete Fourier Tran
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The Discrete Fourier Series 143 den
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The Discrete Fourier Series 145 The
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The Discrete Fourier Series 147 DFS
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Sampling and Reconstruction in the
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The Discrete Fourier Transform 155
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Properties of the Discrete Fourier
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Linear Convolution Using the DFT 18
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The Fast Fourier Transform 187 5.6
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The Fast Fourier Transform 189 Usin
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The Fast Fourier Transform 191 and
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The Fast Fourier Transform 193 Fina
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The Fast Fourier Transform 195 Let
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The Fast Fourier Transform 197 N =2
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The Fast Fourier Transform 199 comp
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Problems 201 Clearly, ˜x 3(n) isdi
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Problems 203 determine the impulse
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Problems 205 and use this property.
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Problems 207 function x3 = circonvf
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Problems 209 where l is an integer.
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Problems 211 2. From the following
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Basic Elements 213 characteristics
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IIR Filter Structures 215 FIGURE 6.
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IIR Filter Structures 217 FIGURE 6.
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IIR Filter Structures 219 for i = 1
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IIR Filter Structures 221 6.2.6 PAR
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IIR Filter Structures 223 Brow = r(
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IIR Filter Structures 225 □ EXAMP
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IIR Filter Structures 227 a1 = 1.00
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FIR Filter Structures 229 FIGURE 6.
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FIR Filter Structures 235 6.3.8 MAT
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Lattice Filter Structures 239 1.000
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Lattice Filter Structures 241 There
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Lattice Filter Structures 243 FIGUR
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Lattice Filter Structures 245 FIGUR
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Lattice Filter Structures 247 funct
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Lattice Filter Structures 249 Solut
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Representation of Numbers 251 new f
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Representation of Numbers 253 rule
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Representation of Numbers 255 Solut
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Representation of Numbers 257 Ten
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Representation of Numbers 259 negat
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Representation of Numbers 261 Two
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Representation of Numbers 263 For t
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Representation of Numbers 265 IEEE
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The Process of Quantization and Err
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Quantization of Filter Coefficients
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Problems 289 z −1 x(n) K 2 2 0.5
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Problems 291 x(n) −1/2 1/2 −2/3
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Problems 293 0.5 1 −1 z −1 2 1
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Problems 295 1. Direct form 2. Line
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Problems 297 P6.24 MATLAB provides
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Problems 299 4. Explain why the mag
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Problems 301 P6.38 An IIR bandstop
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CHAPTER 7 FIR Filter Design We now
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Preliminaries 305 1 + δ 1 1 1 −
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Properties of Linear-phase FIR Filt
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Window Design Techniques 323 where
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Window Design Techniques 325 Rectan
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Window Design Techniques 327 of att
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Page 364 and 365: Frequency Sampling Design Technique
Page 378 and 379: Optimal Equiripple Design Technique
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Analog-to-Digital Filter Transforma
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Lowpass Filter Design Using MATLAB
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Frequency-band Transformations 449
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Problems 461 1 0.8913 Magnitude Res
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Problems 463 1. Determine the value
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Problems 465 function [b,a] =afd(ty
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Problems 467 function [b,a] = mzt(c
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Problems 469 P8.35 Design a highpas
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Problems 471 Using this function, d
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Problems 473 1 0.9 Equiripple |H (e
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Introduction 475 x a (t) ADC F s =
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Decimation by a Factor D 477 as h(n
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Decimation by a Factor D 479 given
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Decimation by a Factor D 481 |X(ω
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Decimation by a Factor D 483 The ou
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Decimation by a Factor D 485 % (c)
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Interpolation by a Factor I 487 Sol
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Interpolation by a Factor I 489 Ide
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Interpolation by a Factor I 491 % (
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Sampling Rate Conversion by a Ratio
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FIR Filter Designs for Sampling Rat
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FIR Filter Structures for Sampling
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Problems 531 P9.3 Consider a signal
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Problems 533 1. Compute and plot th
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Problems 535 3. Let x(n) =cos(0.3π
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Problems 537 3. Using the fir2 func
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Analysis of A/D Quantization Noise
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Round-off Effects in IIR Digital Fi
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Round-off Effects in FIR Digital Fi
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Problems 591 P10.6 Consider the 1st
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Problems 593 which is implemented i
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Applications in Adaptive Filtering
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LMS Algorithm for Coefficient Adjus
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System Identification or System Mod
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Suppression of Narrowband Interfere
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Adaptive Channel Equalization 603 T
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Adaptive Channel Equalization 605 F
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CHAPTER 12 Applications in Communic
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Pulse-Code Modulation 609 called a
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Differential PCM (DPCM) 611 the sig
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Differential PCM (DPCM) 613 digits
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Adaptive PCM and DPCM (ADPCM) 615 a
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Adaptive PCM and DPCM (ADPCM) 617 F
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Delta Modulation (DM) 619 FIGURE 12
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Delta Modulation (DM) 621 FIGURE 12
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Linear Predictive Coding (LPC) of S
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Linear Predictive Coding (LPC) of S
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Dual-tone Multifrequency (DTMF) Sig
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Dual-tone Multifrequency (DTMF) Sig
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Binary Digital Communications 631 F
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Spread-Spectrum Communications 633
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BIBLIOGRAPHY [1] J. W. Cooley and J
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INDEX ’operator, 25 &operator, 26
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INDEX 639 adaptive delta modulation
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INDEX 641 finite-precision numerica
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INDEX 643 round-off effects, 580-59
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INDEX 645 DTFT formula, 152-153 err
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INDEX 647 optimal equiripple design
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INDEX 649 Real-valued exponential s
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INDEX 651 Sinusoidal signals, 83-84
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