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Digital signal processing : a practitioner's approach /
Digital signal processing is essential for improving the accuracy and reliability of a range of engineering systems, including communications, networking, and audio and video applications. Using a combination of programming and mathematical techniques, it clarifies, or standardizes the levels or sta...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Chichester, England ; Hoboken, NJ :
John Wiley,
©2005.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Rangarao, Kaluri Venkata. | |
| 245 | 1 | 0 | |a Digital signal processing : |b a practitioner's approach / |c Kaluri Venkata Rangarao, Ranjan Mallik. |
| 260 | |a Chichester, England ; |a Hoboken, NJ : |b John Wiley, |c ©2005. | ||
| 300 | |a 1 online resource (xvi, 191 pages) : |b illustrations : digital, HTML and PDF files | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover Contents Foreword Preface Acknowledgements 1 Processing of Signals 1.1 Organisation of the Book 1.2 Classification of Signals 1.2.1 Spectral Domain 1.2.2 Random Signals 1.2.3 Periodic Signals 1.3 Transformations 1.3.1 Laplace and Fourier Transforms 1.3.2 The z-Transform and the Discrete Fourier Transform 1.3.3 An Interesting Note 1.4 Signal Characterisation 1.4.1 Non-parametric Spectrum or Fourier Spectrum 1.4.2 Parametric Representation 1.5 Converting Analogue Signals to Digital 1.5.1 Windowing 1.5.2 Sampling 1.5.3 Quantisation 1.5.4 Noise Power 1.6 Signal Seen by the Computing Engine 1.6.1 Mitigating the Problems 1.6.2 Anatomy of a Converter 1.6.3 The Need for Normalised Frequency 1.6.4 Care before Sampling 1.7 It Is Only Numbers 1.7.1 Numerical Methods 1.8 Summary References 2 Revisiting the Basics 2.1 Linearity 2.1.1 Linear Systems 2.1.2 Sinusoidal Inputs 2.1.3 Stability 2.1.4 Shift Invariance 2.1.5 Impulse Response 2.1.6 Decomposing h(k) 2.2 Linear System Representation 2.2.1 Continuous to Discrete 2.2.2 Nomenclature 2.2.3 Difference Equations 2.2.4 Transfer Function 2.2.5 Pole Zero Representation 2.2.6 Continuous to Discrete Domain 2.2.7 State Space Representation 2.2.8 Solution of Linear Difference Equations 2.3 Random Variables 2.3.1 Functions of a Random Variable 2.3.2 Reliability of Systems 2.4 Noise 2.4.1 Noise Generation 2.4.2 Fourier Transform and pdf of Noise 2.5 Propagation of Noise in Linear Systems 2.5.1 Linear System Driven by Arbitrary Noise 2.6 Multivariate Functions 2.6.1 Vectors of More Than Two Dimensions 2.6.2 Functions of Several Variables 2.6.3 System of Equations 2.7 Number Systems 2.7.1 Representation of Numbers 2.7.2 Fixed-Point Numbers 2.7.3 Floating-Point Numbers 2.8 Summary References 3 Digital Filters 3.1 How to Specify a Filter 3.2 Moving-Average Filters 3.2.1 Area under a Curve 3.2.2 Mean of a Given Sequence 3.2.3 Mean over a Fixed Number of Samples 3.2.4 Linear Phase Filters 3.2.5 MA Filter with Complex Coefficients 3.3 Infinite Sequence Generation 3.3.1 Digital Counter 3.3.2 Noise Sequence 3.3.3 Numerically Controlled Oscillator 3.4 Unity-Gain Narrowband Filter 3.5 All-Pass Filter 3.5.1 Interpolation of Data Using an APF 3.5.2 Delay Estimation Using an APF 3.6 Notch Filter 3.6.1 Overview 3.7 Other Autoregressive Filters 3.8 Adaptive Filters 3.8.1 Varying r 3.8.2 Varying p 3.8.3 Criteria 3.8.4 Adaptation 3.9 Demodulating via Adaptive Filters 3.9.1 Demodulation Method 3.9.2 Step Size ̆3.9.3 Performance 3.10 Phase Shift via Adaptive Filter 3.11 Inverse Problems 3.11.1 Model Order Problem 3.11.2 Estimating Filter Coefficients 3.11.3 Target Tracking as an Inverse Problem 3.12 Kalman Filter 3.12.1 Estimating the Rate 3.12.2 Fitting a Sine Curve 3.12.3 Sampling in Space 3.13 Summary References 4 Fourier Transform and Signal Spectrum 4.1 Heterodyne Spectrum Analyser 4.1.1 Spectrum Analyser 4.2 Discrete Fourier Transform 4.3 Decimating the Given Sequence 4.3.1 Sliding DFT 4.4 Fast Fourier Transform 4.4.1 Windowing Effect 4.4.2 Frequency Resolution 4.4.3 Decimation in Time 4.4.4 Decimation in Frequency 4.4.5 Computing Effort Estimate 4.5 Fourier Series Coefficients 4.5.1 Fourier Coefficients 4.6 Convolution by DFT 4.6.1 Circular Convolution 4.7 DFT in Real Time 4.7.1 Vehicle Classification 4.7.2 Instrument Classification 4.8 Frequency Estimation via DFT 4.8.1 Problem Definition 4.8.2 DFT Solution 4.9 Parametric Spectrum in RF Systems 4.9.1 Test Data Generation 4.9.2 Estimating the Parameter Vector 4.10 Summary References 5 Realisation of Digital Filters 5.1 Evolution 5.2 Development Process 5.3 Analogue-to-Digital Converters 5.3.1 Successive Approximation Method 5.3.2 Flash Converters 5.3.3 Sigma Delta Converters 5.3.4 Synchro-to-Digital Converters 5.4 Second-Order BPF 5.4.1 Fix. | |
| 520 | |a Digital signal processing is essential for improving the accuracy and reliability of a range of engineering systems, including communications, networking, and audio and video applications. Using a combination of programming and mathematical techniques, it clarifies, or standardizes the levels or states of a signal, in order to meet the demands of designing high performance digital hardware. Written by authors with a wealth of practical experience working with digital signal processing, this text is an excellent step-by-step guide for practitioners and researchers needing to understand and qu. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Signal processing |x Digital techniques. | |
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| 650 | 6 | |a Traitement du signal |x Techniques numériques. | |
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| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Signals & Signal Processing. |2 bisacsh | |
| 650 | 7 | |a Signal processing |x Digital techniques |2 fast | |
| 655 | 4 | |a Internet Resources. | |
| 700 | 1 | |a Mallik, Ranjan K. | |
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