## Digital Signal ProcessingIntroductionBasic elements of DSP and its requirements, Advantages of digital over analog signal processing, Analysis of LTI systems using z-transform, Introduction to analog filter design, Butterworth and Chebyshev approximation.Analysis of Signals Discrete Fourier transform, Properties, IDFT, Linear filtering methods based on DFT, FFT algorithms, Frequency analysis of discrete time signals, Power density, Energy density, Goertzel algorithm, Application of FFT : DTMF, Spectral analysis, EEG, ECG.FIR Filter Design and Applications Symmetric and Antisymmetric FIR filters, Design of FIR filters using windows, Frequency sampling methods, Alternation theorem in equiripple linear phase FIR filters, FIR differentiators, FIR filter structures - Direct form structures, Cascade form structures, Frequency - Sampling structures, Speech and voice processing, Digital sinusoidal generator.IIR Filters Design and Applications Filter design methods - Approximation of derivatives, Impulse invariance, Bilinear transformation, Characteristics of Butterworth, Chebyshev, Frequency transformations, IIR filter structures - Direct form, Parallel form, Lattice and Lattice-ladder structures, Speech and voice processing, Echo cancellation, Reverberation.Multi-rate Digital Signal Processing Decimation by factor D, Interpolation by factor I, Sampling rate conversion by a rational factor I/D, Filter design and implementation for sampling rate conversion - Direct form FIR filter structures, Time variant filter structures, Sub-band coding of audio signals, Over sampling A/D and D/A, STFT, Wavelet transform.Analysis of Finite Wordlength Effect Quantization process and errors, Analysis of coefficient quantization effects, A/D conversion, Noise analysis, Analysis of arithmetic round-off errors, Dynamic range scaling, Signal to noise ratio in low order IIR filters, Low sensitivity digital filters, Reduction of product round-off errors using error table, Limit cycles in IIR digital filters, Round-off errors in FFT algorithms, Desirable features and architecture of DSP processor. |

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### Contents

Table of Contents | 1-1 |

Chapter6 Analysis of Finite WortHength Effects | 1-6 |

Chapter2 Analysis of Signals 21 to 21 | 2-64 |

Chapter3 FIR Filter Design and Applications 31 to 3 74 | 2-74 |

Assignmenl6 Spectral Analysis of Sinusoidal Signals L 85 to L | 2-88 |

I | 101 |

Chapter4 IIR Filter Design and Applications 41 to 4 126 | 126 |

Chapter2 Analysis of Signals 21 to 2 164 | 164 |

Assignment4 Butterworth Filter Design using Bilinear Transformation L 67 to L | L-67 |

Assignment5 Dual Tone Multifrequency Detection L 80 to L | L-80 |

Aim L85 | L-85 |

Explanation of the Program L 86 | L-86 |

Conclusion L87 | L-87 |

Oral Questions with Answers L 88 | L-88 |

Assignment7 Finite Wordlength Effects L89toL92 | L-89 |

Explanation of the Program L 90 | L-90 |

Chapter5 Multirate Digital Signal Processing 51 to 5 38 | 3-5 |

AppendixB zTransform and DFT Properties B1toB4 | 4-4 |

References R1toR2 | 4-98 |

Chapterwise University Questions with Answers P1toP156 | 5-2 |

Features of Book | 6-34 |

Assignment1 Generation of Sequences L2toL21 | L-2 |

AppendlxB ztransform and DFT Properties B1toB4 | L-4 |

Assignment2 Magnitude and Phase Spectra L 22 to L | L-22 |

Assignment3 FIR Filter Design using Windows L 56 to L | L-56 |

Conclusion L 91 | L-91 |

Assignment8 Sepctrum Analysis of Speech Signal using FFT L 93 to L | L-93 |

Results L94 | L-94 |

Oral Questions with Answers L 95 | L-95 |

Advanced Microprocessors Godse | P-1 |

References R1toR2 | P-2 |

Oral Questions on DSP Processors L 96 to L | P-98 |

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analog filter anticlockwise bilinear transformation butterworth filter calculated causal chebyshev filter circular convolution circularly coefficients complex additions complex multiplications computation of DFT converted cutoff frequency decimation DIF-FFT difference equation digital filter digital signal processing direct computation discrete domain sequence DSP processors DTMF equation becomes Example FFT algorithms filter design FIR filter fourier transform frequency domain frequency response given by equation Goertzel algorithm Hence above equation IIR system implemented impulse response input sequence Kaiser window length linear convolution linear phase lowpass filter LTI system magnitude N-point DFT noise observe obtained output passband point DFT pole zero plot quantization rad/sec sampling rate sequence x(n shift shown in Fig shows signal flow graph Solution spectrum stable Step stopband summation system function Taking inverse z-transform Taking z-transform Theory Questions transfer function Transition band unit circle unit sample response z-plane