Introduction To Discrete Time Signal Processing
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Discrete-time Signal Processing
Índice: 1. Introduction. 2. Discrete-Time Signals and Systems. Introduction. Discrete-time Signals: Sequences. Discrete-time Systems. Linear Time-Invariant Systems. Properties of Linear Time-Invariant Systems. Linear Constant-Coefficient Difference Equations. Frequency-Domain Representation of Discrete-Time Signals and Systems. Representation of Sequence by Fourier Transforms. Symmetry Properties of the Fourier Transform. Fourier Transform Theorems. Discrete-Time Random Signals. Summary. 3. The z-Transform. Introduction. The z-Transform. Properties of the Region of Convergence for the z-Transform. The Inverse z-Transform. z-Transform Properties. Summary. 4. Sampling of Continuous-Time Signals. Introduction. Periodic Sampling. Frequency-Domain Representation of Sampling. Reconstruction of a Bandlimited Signal from its Samples. Discrete-Time Processing of Continuous-Time Signals. Continuous-Time Processing of Discrete-Time Signals. Changing the Sampling Rate Using Discrete-Time Processing. Practical Considerations. Oversampling and Noise Shaping. Summary. 5. Transform Analysis of Linear Time-Invariant Systems. Introduction. The Frequency Response of LTI Systems. System Functions for Systems Characterized by Linea. Frequency Response for Rational System Functions. Relationship Between Magnitude and Phase. All-Pass Systems. Minimum-Phase Systems. Linear Systems with Generalized Linear Phase. Summary. 6. Structures for Discrete-Time Systems. Introduction. Block Diagram Representation of Linear Constant-Coefficient Difference Equations. Signal Flow Graph Representation of Linear Constant-Coefficient Difference Equations. Basic Structures for IIR Systems. Transposed Forms. Basic Network Structures for FIR Systems. Overview of Finite-Precision Numerical Effects. The Effects of Coefficient Quantization. Effects of Roundoff Noise in Digital Filters. Zero-Input Limit Cycles in Fixed-Point Realizations of IIR Digital Filters. Summary. 7. Filter Design Techniques. Introduction. Design of Discrete-Time IIR Filters from Continuous-Time Filters. Design of FIR Filters by Windowing. Examples of FIR Filter Design by the Kaiser Window Method. Optimum Approximations of FIR Filters. Examples of FIR Equiripple Approximation. Comments on IIR and FIR Digital Filters. Summary. 8. The Discrete Fourier Transform. Introduction. Representation of Periodic Sequences: the Discrete Fourier Series. Summary of Properties of the DFS Representation of Periodic Sequences. The Fourier Transform of Periodic Signals. Sampling the Fourier Transform. Fourier Representation of Finite-Duration Sequences: The Discrete-Fourier Transform. Properties of the Discrete Fourier Transform. Summary of Properties of the Discrete Fourier Transform. Linear Convolution Using the Discrete Fourier Transform. The Discrete Cosine Transform (DCT). Summary. 9. Computation of the Discrete Fourier Transform. Introduction.
Discrete-Time Speech Signal Processing
Author: Thomas F. Quatieri
language: en
Publisher: Pearson Education
Release Date: 2008-11-10
Essential principles, practical examples, current applications, and leading-edge research. In this book, Thomas F. Quatieri presents the field's most intensive, up-to-date tutorial and reference on discrete-time speech signal processing. Building on his MIT graduate course, he introduces key principles, essential applications, and state-of-the-art research, and he identifies limitations that point the way to new research opportunities. Quatieri provides an excellent balance of theory and application, beginning with a complete framework for understanding discrete-time speech signal processing. Along the way, he presents important advances never before covered in a speech signal processing text book, including sinusoidal speech processing, advanced time-frequency analysis, and nonlinear aeroacoustic speech production modeling. Coverage includes: Speech production and speech perception: a dual view Crucial distinctions between stochastic and deterministic problems Pole-zero speech models Homomorphic signal processing Short-time Fourier transform analysis/synthesis Filter-bank and wavelet analysis/synthesis Nonlinear measurement and modeling techniques The book's in-depth applications coverage includes speech coding, enhancement, and modification; speaker recognition; noise reduction; signal restoration; dynamic range compression, and more. Principles of Discrete-Time Speech Processing also contains an exceptionally complete series of examples and Matlab exercises, all carefully integrated into the book's coverage of theory and applications.
Introductory Signal Processing
A valuable introduction to the fundamentals of continuous and discrete time signal processing, this book is intended for the reader with little or no background in this subject. The emphasis is on development from basic principles. With this book the reader can become knowledgeable about both the theoretical and practical aspects of digital signal processing.Some special features of this book are: (1) gradual and step-by-step development of the mathematics for signal processing, (2) numerous examples and homework problems, (3) evolutionary development of Fourier series, Discrete Fourier Transform, Fourier Transform, Laplace Transform, and Z-Transform, (4) emphasis on the relationship between continuous and discrete time signal processing, (5) many examples of using the computer for applying the theory, (6) computer based assignments to gain practical insight, (7) a set of computer programs to aid the reader in applying the theory.