Verified Signal Processing Algorithms in Matlab and C: Advised by Israel Greiss

Description

This book is written for engineers who need to develop algorithms used for signal processing and/or implement algorithms using the C programming language or Matlab. The book features a rich collection of recipes for applied signal processing such as FIR, IIR, FFT, correlation, complex FIR, adaptive filters and others. The book applies to those who want to implement in the shortest time to market working systems that are built from a collection of building blocks implemented in an FPGA firmware or C language software, running on an SBC or DSP. Structured as an instantly applicable guide, the author covers a wide collection of required solutions to common encountered problems with a software guide. All Codes in the book are verified and processing times for all C codes are specified, enabling the reader to estimate processing time on his own target, by comparing it to the I5 2.9 GHz CPU used here.  Endorsements:  “Your book bridges a gap between theory and implementation on hardware - which is a topic relevant to many in industry and many students who are targeting the digital signal processing industry (including communications and robotics)” Professor Alfred Hero, University of Michigan, Ann Arbor, USA “I believe you that for many engineers the book will be practical” Professor Anthony J. Weiss, Tel Aviv University, Israel Preface Acknowledgment Contents Chapter 1: Overview of Signal Detection 1.1 Introduction 1.2 About Signal Detection 1.3 Conclusions Chapter 2: Measures for Verification and Implementation of Algorithms 2.1 Introduction 2.2 Measures Details 2.2.1 Algorithm Verification in Frequency 2.2.2 Preparing Coefficients File for C Software 2.2.3 Algorithm Verification in Time 2.2.4 Algorithm Transient Time Measurement 2.2.5 Algorithm Processing Time Measurement 2.3 Conclusions Chapter 3: Narrow Band & Wide Band Processing Basics 3.1 Narrow Band Processing 3.1.1 Introduction 3.1.2 Numerically Controlled Oscillator 3.1.3 Finite Impulse Response Decimators 3.1.4 Low Decimation Ratio Finite Impulse Response Filters 3.1.5 Higher Decimation Ratio Finite Impulse Response Filters 3.1.5.1 Cascaded Integrator Comb Decimator Design 3.1.5.2 Finite Impulse Response Decimator by 4 Design 3.1.5.3 Compensator Design 3.1.6 Conclusions 3.2 Wide Band Processing 3.2.1 Introduction 3.2.2 Shaping Windows 3.2.3 Designing Self Made Windows 3.2.4 Fast Fourier Transform 3.2.5 Fast Fourier Transform Implementation 3.2.5.1 Bit Reversed Order 3.2.5.2 Radix 2 Twiddle Factors 3.2.5.3 Fast Fourier Transform Radix 2 Implementation 3.2.5.4 Digit Reversed Order 3.2.5.5 Radix 4 Twiddle Factors 3.2.5.6 Fast Fourier Transform Radix 4 Implementation 3.2.6 Implementing Large Fast Fourier Transform by Smaller Ones 3.2.6.1 Implementing Fast Fourier Transform size N by 16 FFTs Size N/16 3.2.6.2 Implementing Fast Fourier Transform size N by 4 FFTs size N/4 3.2.6.3 Implementing Fast Fourier Transform Size 3*2^N 3.2.6.4 Relative Error Analysis 3.2.7 Conclusions References Chapter 4: Complex Finite Impulse Response Filters 4.1 Introduction 4.2 Complex Finite Impulse Response Filter Design 4.2.1 Modified Low Pass Filter Design Method 4.2.2 Matlab Direct Complex Filter Design Method 4.2.3 Preferred Design Method 4.2.4 Property of Complex Filters 4.2.5 Implementation of Complex Filters 4.3 Conclusions Chapter 5: Infinite Impulse Response Filters 5.1 Introduction 5.2 Infinite Impulse Response Filter Design 5.2.1 Low Pass Filter Design 5.2.1.1 Sensitivity to Quantization of Coefficients 5.2.1.2 Group Delay Assessment 5.2.1.3 Comparing Low Pass Infinite Impulse Response Filter & FIR 5.2.2 High Pass Filter Design 5.2.2.1 Sensitivity to Quantization of Coefficients 5.2.2.2 Group Delay Assessment 5.2.2.3 Comparing High Pass Infinite Impulse Response Filter & FIR 5.2.3 Band Stop Filter Design 5.2.3.1 Sensitivity to Quantization of Coefficients 5.2.3.2 Group Delay Assessment 5.2.3.3 Comparing Band Stop Infinite Impulse Response Filter & FIR 5.2.4 All Pass Filter Design 5.2.5 Band Pass Filter Design 5.2.5.1 Sensitivity to Quantization of Coefficients 5.2.5.2 Group Delay Assessment 5.2.5.3 Comparing Band Pass Infinite Impulse Response Filter & FIR 5.3 Conclusions Chapter 6: Non-Linear and Batch Filters 6.1 Introduction 6.2 Median Filter 6.3 Batch Filter with Comparison to Median Filter 6.4 Conclusions Chapter 7: Interpolators 7.1 Introduction 7.2 Interpolator Design 7.2.1 Fractional Interpolation/Decimation 7.2.1.1 Polyphase Filter Design 7.2.1.2 Fractional Interpolation/Decimation Using Matlab interp1 Method 7.3 Conclusions Chapter 8: Direct Digital Synthesis 8.1 Introduction 8.2 Direct Digital Synthesizer Details 8.2.1 Frequency Modulation of a Direct Digital Synthesizer 8.2.2 Receiver—Frequency Demodulator for Verification 8.2.3 Amplitude Modulation of a Direct Digital Synthesizer 8.2.4 Receiver—Amplitude Demodulator for Verification 8.3 Conclusions Chapter 9: Inverse Fast Fourier Transform 9.1 Introduction 9.2 Inverse Fast Fourier Transform Details 9.3 Inverse Fast Fourier Transform Implementation 9.4 Frequency Modulation of Inverse Fast Fourier Transform Output 9.5 Conclusions Reference Chapter 10: Hilbert Transform Chapter 11: Channelizer 11.1 Introduction 11.2 Channelizer Fundamentals 11.2.1 Comparing Channelizer and Narrow Band Processing Times 11.2.2 Channelizer Design Considerations 11.3 Conclusions Chapter 12: Correlation 12.1 Introduction 12.2 Correlation Details 12.2.1 Fast Correlation by Using Fast Fourier Transform 12.3 Pattern Recognition 12.4 Conclusions Chapter 13: Adaptive Filters 13.1 Introduction 13.2 Equalizers 13.2.1 Least Mean Squares Algorithm 13.2.2 Normalized Least Mean Squares Algorithm 13.2.3 Multi-input Equalizer 13.3 Interference Cancellation 13.3.1 Least Mean Squares Cancelling Algorithm 13.3.2 Recursive Least Squares Cancelling Algorithm 13.4 Conclusions Reference Chapter 14: Unequally Spaced Sampling 14.1 Introduction 14.2 Modified Lomb–Scargle Algorithm 14.3 Algorithm Performance 14.4 Algorithm Quality Factor 14.5 Algorithm Sensitivity to Interference 14.6 Algorithm Implementation in C 14.7 Conclusions References Chapter 15: Encountered Problems in Signal Processing & Solutions 15.1 Introduction 15.2 When Input Signal Includes Spikes 15.3 When Input Signal Includes Fast Transitions 15.4 Algorithms Processing Time Improvement 15.5 Mean Center Frequency Estimation of Signals 15.5.1 Mean Center Frequency Estimation for Multiple Signals 15.5.2 Mean Center Frequency Estimation for a Single Channel 15.6 Power Level Estimation 15.7 Noise Floor Estimation 15.8 Bandwidth Estimation 15.9 Automatic Level Control 15.10 Frequency Response Estimation 15.11 Group Delay Estimation 15.12 Conclusions Related Software Index