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" Digital signal processing : "
Li Tan, Jean Jiang
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BL
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| Record Number
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622411
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dltt
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| Main Entry
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Tan, Li,1963-
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| Title & Author
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Digital signal processing : : fundamentals and applications /\ Li Tan, Jean Jiang
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| Edition Statement
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Second edition
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| Page. NO
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xv, 876 pages :: illustrations ;; 24 cm
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| ISBN
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9780124158931 (hbk.)
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: 0124158935 (hbk.)
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| Bibliographies/Indexes
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Includes bibliographical references (p. 857-859) and index
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| Contents
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Machine generated contents note: 1.1.Basic Concepts of Digital Signal Processing -- 1.2.Basic Digital Signal Processing Examples in Block Diagrams -- 1.2.1.Digital Filtering -- 1.2.2.Signal Frequency (Spectrum) Analysis -- 1.3.Overview of Typical Digital Signal Processing in Real-World Applications -- 1.3.1.Digital Crossover Audio System -- 1.3.2.Interference Cancellation in Electrocardiography -- 1.3.3.Speech Coding and Compression -- 1.3.4.Compact-Disc Recording System -- 1.3.5.Vibration Signature Analysis for Defective Gear Teeth -- 1.3.6.Digital Photo Image Enhancement -- 1.4.Digital Signal Processing Applications -- 1.5.Summary -- 2.1.Sampling of Continuous Signal -- 2.2.Signal Reconstruction -- 2.2.1.Practical Considerations for Signal Sampling: Anti-Aliasing Filtering -- 2.2.2.Practical Considerations for Signal Reconstruction: Anti-Image Filter and Equalizer -- 2.3.Analog-to-Digital Conversion, Digital-to-Analog Conversion, and Quantization -- 2.4.Summary -- 2.5.MATLAB Programs -- 2.6.Problems -- 3.1.Digital Signals -- 3.1.1.Common Digital Sequences -- 3.1.2.Generation of Digital Signals -- 3.2.Linear Time-Invariant, Causal Systems -- 3.2.1.Linearity -- 3.2.2.Time Invariance -- 3.2.3.Causality -- 3.3.Difference Equations and Impulse Responses -- 3.3.1.Format of the Difference Equation -- 3.3.2.System Representation Using Its Impulse Response -- 3.4.Bounded-In and Bounded-Out Stability -- 3.5.Digital Convolution -- 3.6.Summary -- 3.7.Problem -- 4.1.Discrete Fourier Transform -- 4.1.1.Fourier Series Coefficients of Periodic Digital Signals -- 4.1.2.Discrete Fourier Transform Formulas -- 4.2.Amplitude Spectrum and Power Spectrum -- 4.3.Spectral Estimation Using Window Functions -- 4.4.Application to Signal Spectral Estimation -- 4.5.Fast Fourier Transform -- 4.5.1.Decimation-in-Frequency Method -- 4.5.2.Decimation-in-Time Method -- 4.6.Summary -- 4.7.Problem -- 5.1.Definition -- 5.2.Properties of the z-Transform -- 5.3.Inverse z-Transform -- 5.3.1.Partial Fraction Expansion Using MATLAB -- 5.4.Solution of Difference Equations Using the z-Transform -- 5.5.Summary -- 5.6.Problems -- 6.1.The Difference Equation and Digital Filtering -- 6.2.Difference Equation and Transfer Function -- 6.2.1.Impulse Response, Step Response, and System Response -- 6.3.The z-Plane Pole-Zero Plot and Stability -- 6.4.Digital Filter Frequency Response -- 6.5.Basic Types of Filtering -- 6.6.Realization of Digital Filters -- 6.6.1.Direct-Form I Realization -- 6.6.2.Direct-Form II Realization -- 6.6.3.Cascade (Series) Realization -- 6.6.4.Parallel Realization -- 6.7.Application: Signal Enhancement and Filtering -- 6.7.1.Pre-Emphasis of Speech -- 6.7.2.Bandpass Filtering of Speech -- 6.7.3.Enhancement of ECG Signal Using Notch Filtering -- 6.8.Summary -- 6.9.Problem -- 7.1.Finite Impulse Response Filter Format -- 7.2.Fourier Transform Design -- 7.3.Window Method -- 7.4.Applications: Noise Reduction and Two-Band Digital Crossover -- 7.4.1.Noise Reduction -- 7.4.2.Speech Noise Reduction -- 7.4.3.Noise Reduction in Vibration Signals -- 7.4.4.Two-Band Digital Crossover -- 7.5.Frequency Sampling Design Method -- 7.6.Optimal Design Method -- 7.7.Realization Structures of Finite Impulse Response Filters -- 7.7.1.Transversal Form -- 7.7.2.Linear Phase Form -- 7.8.Coefficient Accuracy Effects on Finite Impulse Response Filters -- 7.9.Summary of FIR Design Procedures and Selection of FIR Filter Design Methods in Practice -- 7.10.Summary -- 7.11.MATLAB Programs -- 7.12.Problems -- 8.1.Infinite Impulse Response Filter Format -- 8.2.Bilinear Transformation Design Method -- 8.2.1.Analog Filters Using Lowpass Prototype Transformation -- 8.2.2.Bilinear Transformation and Frequency Warping -- 8.2.3.Bilinear Transformation Design Procedure -- 8.3.Digital Butterworth and Chebyshev Filter Designs -- 8.3.1.Lowpass Prototype Function and Its Order -- 8.3.2.Lowpass and Highpass Filter Design Examples -- 8.3.3.Bandpass and Bandstop Filter Design Examples -- 8.4.Higher-Order Infinite Impulse Response Filter Design Using the Cascade Method -- 8.5.Application: Digital Audio Equalizer -- 8.6.Impulse-Invariant Design Method -- 8.7.Pole-Zero Placement Method for Simple Infinite Impulse Response Filters -- 8.7.1.Second-Order Bandpass Filter Design -- 8.7.2.Second-Order Bandstop (Notch) Filter Design -- 8.7.3.First-Order Lowpass Filter Design -- 8.7.4.First-Order Highpass Filter Design -- 8.8.Realization Structures of Infinite Impulse Response Filters -- 8.8.1.Realization of Infinite Impulse Response Filters in Direct-Form I and Direct-Form II -- 8.8.2.Realization of Higher-Order Infinite Impulse Response Filters via the Cascade Form -- 8.9.Application: 60-Hz Hum Eliminator and Heart Rate Detection Using Electrocardiography -- 8.10.Coefficient Accuracy Effects on Infinite Impulse Response Filters -- 8.11.Application: Generation and Detection of DTMF Tones Using the Goertzel Algorithm -- 8.11.1.Single-Tone Generator -- 8.11.2.Dual-Tone Multifrequency Tone Generator -- 8.11.3.Goertzel Algorithm -- 8.11.4.Dual-Tone Multifrequency Tone Detection Using the Modified Goertzel Algorithm -- 8.12.Summary of Infinite Impulse Response (IIR) Design Procedures and Selection of the IM Filter Design Methods in Practice -- 8.13.Summary -- 8.14.Problem -- 9.1.Digital Signal Processor Architecture -- 9.2.Digital Signal Processor Hardware Units -- 9.2.1.Multiplier and Accumulator -- 9.2.2.Shifters -- 9.2.3.Address Generators -- 9.3.Digital Signal Processors and Manufacturers -- 9.4.Fixed-Point and Floating-Point Formats -- 9.4.1.Fixed-Point Format -- 9.4.2.Floating-Point Format -- 9.4.3.IEEE Floating-Point Formats -- 9.4.5.Fixed-Point Digital Signal Processors -- 9.4.6.Floating-Point Processors -- 9.5.Finite Impulse Response and Infinite Impulse Response Filter Implementations in Fixed-Point Systems -- 9.6.Digital Signal Processing Programming Examples -- 9.6.1.Overview of TMS320C67x DSK -- 9.6.2.Concept of Real-Time Processing -- 9.6.3.Linear Buffering -- 9.6.4.Sample C Programs -- 9.7.Summary -- 9.8.Problems -- 10.1.Introduction to Least Mean Square Adaptive Finite Impulse Response Filters -- 10.2.Basic Wiener Filter Theory and Least Mean Square Algorithm -- 10.3.Applications: Noise Cancellation, System Modeling, and Line Enhancement -- 10.3.1.Noise Cancellation -- 10.3.2.System Modeling -- 10.3.3.Line Enhancement Using Linear Prediction -- 10.4.Other Application Examples -- 10.4.1.Canceling Periodic Interferences Using Linear Prediction -- 10.4.2.Electrocardiography Interference Cancellation -- 10.4.3.Echo Cancellation in Long-Distance Telephone Circuits -- 10.5.Laboratory Examples Using the TMS320C6713 DSK -- 10.6.Summary -- 10.7.Problems -- 11.1.Linear Midtread Quantization -- 11.2.[æ]-law Companding -- 11.2.1.Analog [æ]-Law Companding -- 11.2.2.Digital [æ]-Law Companding -- 11.3.Examples of Differential Pulse Code Modulation (DPCM), Delta Modulation, and Adaptive DPCM G.721 -- 11.3.1.Examples of Differential Pulse Code Modulation and Delta Modulation -- 11.3.2.Adaptive Differential Pulse Code Modulation G.721 -- 11.4.Discrete Cosine Transform, Modified Discrete Cosine Transform, and Transform Coding in MPEG Audio -- 11.4.1.Discrete Cosine Transform -- 11.4.2.Modified Discrete Cosine Transform -- 11.4.3.Transform Coding in MPEG Audio -- 11.5.Laboratory Examples of Signal Quantization Using the TMS320C6713 DSK -- 11.6.Summary -- 11.7.MATLAB Programs -- 11.8.Problems -- 12.1.Multirate Digital Signal Processing Basics -- 12.1.1.Sampling Rate Reduction by an Integer Factor -- 12.1.2.Sampling Rate Increase by an Integer Factor -- 12.1.3.Changing the Sampling Rate by a Noninteger Factor L/M -- 12.1.4.Application: CD Audio Player -- 12.1.5.Multistage Decimation -- 12.2.Polyphase Filter Structure and Implementation -- 12.3.Oversampling of Analog-to-Digital Conversion -- 12.3.1.Oversampling and Analog-to-Digital Conversion Resolution -- 12.3.2.Sigma-Delta Modulation Analog-to-Digital Conversion -- 12.4.Application
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Example: CD Player -- 12.5.Undersampling of Bandpass Signals -- 12.6.Sampling Rate Conversion Using the TMS320C6713 DSK -- 12.7.Summary -- 12.8.Problems -- 13.1.Subband Coding Basics -- 13.2.Subband Decomposition and Two-Channel Perfect Reconstruction Quadrature Mirror Filter Bank -- 13.3.Subband Coding of Signals -- 13.4.Wavelet Basics and Families of Wavelets -- 13.5.Multiresolution Equations -- 13.6.Discrete Wavelet Transform -- 13.7.Wavelet Transform Coding of Signals -- 13.8.MATLAB Programs -- 13.9.Summary -- 13.10.Problems -- 14.1.Image Processing Notation and Data Formats -- 14.1.1.8-Bit Gray Level Images -- 14.1.2.24-bit Color Images -- 14.1.3.8-Bit Color Images -- 14.1.4.Intensity Images -- 14.1.5.Red, Green, and Blue Components and Grayscale Conversion -- 14.1.6.MATLAB Functions for Format Conversion -- 14.2.Image Histogram and Equalization -- 14.2.1.Grayscale Histogram and Equalization -- 14.2.2.24-Bit Color Image Equalization -- 14.2.3.8-Bit Indexed Color Image Equalization -- 14.2.4.MATLAB Functions for Equalization -- 14.3.Image Level Adjustment and Contrast -- 14.3.1.Linear Level Adjustment -- 14.3.2.Adjusting the Level for Display -- 14.3.3.MATLAB Functions for Image Level Adjustment -- 14.4.Image Filtering Enhancement -- 14.4.1.Lowpass Noise Filtering -- 14.4.2.Median Filtering -- 14.4.3.Edge Detection -- 14.4.4.MATLAB Functions for Image Filtering -- 14.5.Image Pseudo-Color Generation and Detection -- 14.6.Image Spectra -- 14.7.Image Compression by Discrete Cosine Transform -- 14.7.1.Two-Dimensional Discrete Cosine Transform -- 14.7.2.Two-Dimensional JPEG Grayscale Image Compression Example -- 14.7.3.JPEG Color Image Compression -- 14.7.4.Image Compression Using Wavelet Transform Coding -- 14.8.Creating a Video Sequence by Mixing Two Images -- 14.9.Video Signal Basics -- 14.9.1.Analog Video -- 14.9.2.Digital Video -- 14.10.Motion Estimation in Video -- 14.11.Summary -- 14.12.Problems
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| Abstract
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"Bridging the gap between theory and application, this text covers all the main areas of modern DSP. Principles, applications, and hardware implementation issues are presented, and a wealth of worked examples and end of chapter exercises provide the opportunity for self-learning. Throughout the book emphasis is placed on applications to signal, image, and video processing, and real time implementation of DSP algorithms using DSP processors is highlighted."--Back Cover
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| Subject
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Signal processing-- Digital techniques
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| Dewey Classification
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621.3822
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| LC Classification
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TK5102.9.T36 2013
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| Added Entry
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Jiang, Jean
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