Digital signal processing: a breadth-first approach

The subject of Digital Signal Processing (DSP) is enormously complex, involving many concepts, probabilities, and signal processing that are woven together in an intricate manner. To cope with this scope and complexity, many DSP texts are often organized around the znumerical examplesy of a communication system. With such organization, readers can see through the complexity of DSP, they learn about the distinct concepts and protocols in one part of the communication system while seeing the big picture of how all parts fit together. From a pedagogical perspective, our personal experience has been that such approach indeed works well. Based on the authors' extensive experience in teaching and research, Digital Signal Processing: a breadth-first approach is written with the reader in mind. The book is intended for a course on digital signal processing, for seniors and undergraduate students. The subject has high popularity in the field of electrical and computer engineering, and the authors consider all the needs and tools used in analysis and design of discrete time systems for signal processing. Key features of the book include: * The extensive use of MATLAB based examples to illustrate how to solve signal processing problems. The textbook includes a wealth of problems, with solutions * Worked-out examples have been included to explain new and difficult concepts, which help to expose the reader to real-life signal processing problems * The inclusion of FIR and IIR filter design further enrich the contents.

7.3.5.1 Gray-Markel method of IIR lattice structure for ladder coefficients 328 7.3.5.2 Calculation of ladder coefficients using Gray-Markel method 329 7.4 Implementation of Filters 330 7.5 Problems and Solutions 332 8 Introduction to Digital Filters 359 8.1 Introduction 359 8.1.1 Types of Filters 359 8.1.2 Classification of Filters DevelopmentWise 360 8.1.3 Analog Filters 360 8.1.4 Types of Analog Filter 360 8.2 Digital Filters 360 8.3 Importance and Advantages 361 8.4 Disadvantages 361 8.4.1 Speed Limitation 361 8.4.2 FiniteWord-Length Effects 362 8.4.3 Limit Cycles 362 8.4.4 Long Design and Development Times 363 8.5 Types of Digital Filters 363 8.5.1 FIR (Finite Impulse Response) Filters 363 8.5.2 IIR (Infinite Impulse Response) Filters 364 8.6 Choosing between FIR and IIR Filters 364 8.7 Tolerance Scheme of FIR and IIR Filters 365 8.7.1 FIR Filters 365 8.7.2 IIR Filters 367 8.8 FIR and IIR Filter Design Stages 368 8.8.1 Filter Specification 368 8.8.2 Coefficient Calculation 368 8.8.3 Realization 369 8.8.4 Analysis of FiniteWord-Length Effects 369 8.8.5 Implementation 369 8.9 Filters Coefficient Calculation Methods 369 8.9.1 FIR Filters Coefficient Calculation Methods 369 8.9.2 IIR Filters Coefficient Calculation Methods 370 8.9.3 Summary of Filters Coefficient Calculation Methods 370 9 Step-by-Step Design of Digital FIR Filters 373 9.1 Introduction 373 9.2 Why is it Called the Finite Impulse Response Filter? 373 9.2.1 Features of FIR Filters 374 9.2.2 Linear-Phase Implications 377 9.2.2.1 Effect of phase distortion on signals 377 9.2.2.2 Phase delay 377 9.2.2.3 Group delay 378 9.3 Type of FIR Filters 381 9.3.1 Type-1 FIR Filter (Length of the filter N is odd) 381 9.3.2 Type-II FIR Filter (Length of the filter N is even) 383 9.3.3 Type III-FIR Filter (Length of the filter N is odd) 384 9.3.4 Type-IV FIR Filter (Length of the filter N is even) 386 9.4 Basic Principle of FIR Filter Design 396 9.4.1 Windows Used in FIR Filters 397 9.4.1.1 Windowing a signal 398 9.4.1.2 Rectangular window 398 9.4.1.3 Hanning window 398 9.4.1.4 Hamming window 400 9.5 Design of FIR Filter using the Window Method 402 9.5.1 To Find the Filter Coefficients usingWindow 405 9.5.2 Filter Design Steps for Non-causal Filters 405 9.5.3 Filter Design Steps for Causal Filters 406 9.5.4 Designing Other Types of FIR Filters 409 9.5.5 Smearing Effect 415 9.5.6 KaiserWindow 419 9.5.6.1 Procedure to FIR filter design using Kaiser windows 420 9.5.7 Comparison ofWindow Methods 421 9.5.8 Analysis of Different FIR Filter Types 421 9.5.9 Conclusion for the Types of FIR Filter 422 9.5.10 Advantages/Disadvantages of the Window Method 422 9.6 Problems and Solutions 422 10 Step-by-Step Design of IIR Filters 457 10.1 Introduction 457 10.2 Analog Prototype Filters 457 10.2.1 Preview of Butterworth Filter 458 10.2.2 Preview of Chebyshev Filter 460 10.2.3 Preview of Elliptic filter 462 10.3 Basic Structure of IIR Filters 462.

Preface xix Acknowledgments xxiii -- List of Figures xxv -- List of Tables xxxi -- List of Abbreviations xxxiii -- 1 Introduction 1 -- 1.1 Concept of Signal Processing 1 -- 1.1.1 Analog Signal Processing 1 -- 1.1.2 Digital Signal Processing 1 -- 1.2 Roots of DSP 2 -- 1.3 Advantages of DSP 3 -- 1.4 Basic Blocks of Signal Processing System 3 -- 1.5 DSP Key Operations 4 -- 1.6 Classification of Signals 4 -- 1.6.1 Continuous-Time versus Discrete-Time Signals 4 -- 1.6.2 Continuous-Valued versus Discrete-Valued Signals 4 -- 1.6.3 Deterministic versus Random Signals 5 -- 1.6.4 Multi-Channel and Multi-Dimensional Signals 5 -- 1.7 Application of DSP 6 -- 1.7.1 Telecommunications 6 -- 1.7.1.1 Multiplexing 6 -- 1.7.1.2 Compression 7 -- 1.7.1.3 Echo control 7 -- 1.7.2 Audio Signal Processing 7 -- 1.7.2.1 Speech generation 7 -- 1.7.2.2 Speech recognition 7 -- 1.7.3 Echo Location 7 -- 1.7.3.1 Radar (RAdio Detection And Ranging) 8 -- 1.7.3.2 Sonar (SOund Navigation And Ranging) 8 -- 1.7.3.3 Reflection seismology 9 -- 1.7.4 Image Processing 9 -- 1.7.4.1 Medical 9 -- 1.7.4.2 Space 10 -- 2 Signals and Systems (Continuous and Discrete) 11 -- 2.1 Introduction 11 -- 2.2 CT Signals 12 -- 2.2.1 Unit Imp…