Smartphone-Based Real-Time Digital Signal Processing: Second Edition (Synthesis Lectures on Signal Processing, 16)

✍ Scribed by Nasser Kehtarnavaz, Abhishek Sehgal, Shane Parris

• Publisher: Morgan & Claypool Publishers
• Tongue: English
• Leaves: 169
• Category: Library

✦ Synopsis

Real-time or applied digital signal processing courses are offered as follow-ups to conventional or theory-oriented digital signal processing courses in many engineering programs for the purpose of teaching students the technical know-how for putting signal processing algorithms or theory into practical use. These courses normally involve access to a teaching laboratory that is equipped with hardware boards, in particular DSP boards, together with their supporting software. A number of textbooks have been written discussing how to achieve real-time implementation on these hardware boards. This book discusses how to use smartphones as hardware boards for real-time implementation of signal processing algorithms as an alternative to the hardware boards that are used in signal processing laboratory courses. The fact that mobile devices, in particular smartphones, have become powerful processing platforms led to the development of this book enabling students to use their own smartphones to run signal processing algorithms in real-time considering that these days nearly all students possess smartphones. Changing the hardware platforms that are currently used in applied or real-time signal processing courses to smartphones creates a truly mobile laboratory experience or environment for students. In addition, it relieves the cost burden associated with using dedicated signal processing boards noting that the software development tools for smartphones are free of charge and are well-maintained by smartphone manufacturers. This book is written in such a way that it can be used as a textbook for real-time or applied digital signal processing courses offered at many universities. Ten lab experiments that are commonly encountered in such courses are covered in the book. This book is written primarily for those who are already familiar with signal processing concepts and are interested in their real-time and practical aspects. Similar to existing real-time courses, knowledge of C programming is assumed. This book can also be used as a self-study guide for those who wish to become familiar with signal processing app development on either Android or iPhone smartphones.

✦ Table of Contents

Preface
Introduction
Smartphone Implementation Tools
Smartphone Implementation Shells
Android Implementation
Iphone Implementation
Overview of ARM Processor Architecture
Data Flow and Registers
Organization of Chapters
Software Package of Lab Codes
References
Android Software Development Tools
Installation Steps
Java JDK
Android Studio Bundle and Native Development Kit
Environment Variable Configuration
Android Studio Configuration
Android Emulator Configuration
Android Studio Setup for Mac
LAB 1: Getting Familiar with Android Software Tools
Lab Exercise
iOS Software Development Tools
App Development
Setting-up App Environment
Creating Layout
Implementing C Codes
Executing C Codes Via Objective-C
Swift Programming Language
LAB 2: iPhone App Debugging
Lab Exercise
Analog-to-Digital Signal Conversion
Sampling
Quantization
References
LAB 3: Android Audio Signal Sampling
Demo Application
Application Code
Recording
Processing.Java
JNI Native C Code
Superpowered SDK
Multi-Threading
Multi-Rate Signal Processing
Lab Exercises
LAB 4: iPhone Audio Signal Sampling
App Source Code
App Code Discussion
Recording
Native C Code
Multi-Threading
Multi-Rate Signal Processing
Lab Exercises
Fixed-Point vs. Floating-Point
Q-Format Number Representation
Floating-Point Number Representation
Overflow and Scaling
Some Useful Arithmetic Operations
Division
Sine and Cosine
Square-Root
LAB 5: Fixed-Point and Floating-Point Operations
App Structure
NEON SIMD Coprocessor
Lab Exercises
References
Real-Time Filtering
FIR Filter Implementation
Circular Buffering
Frame Processing
Finite Word Length Effect
References
LAB 6: Real-Time FIR Filtering, Quantization Effect, and Overflow
Filter Design
ARM Overflow Detection
Lab Exercises
Adaptive Filtering
Infinite Impulse Response Filters
Adaptive Filtering
References
LAB 7: IIR Filtering and Adaptive FIR Filtering
IIR Filter Design
Adaptive FIR Filter
Lab Exercises
Frequency Domain Transforms
Fourier Transforms
Discrete Fourier Transform
Fast Fourier Transform
Leakage
Windowing
Overlap Processing
Reconstruction
Inverse Fourier Transform
Overlap-Add Reconstruction
References
LAB 8: Frequency Domain Transforms–DFT and FFT
Lab Exercises
Code Optimization
Code Timing
Linear Convolution
Compiler Options
Efficient C Code Writing
Architecture-SpecifiC Optimizations
Target Architecture
Arm Hardware Capabilities
Neon Intrinsics
LAB 9: Code Optimization
Compiler Options
Target Architecture (Android Only)
Code Modification
References
Implementation Via Matlab Coder
Matlab Function Design
Test Bench
Code Generation
Source Code Integration
Summary
References
LAB 10: Matlab Coder Implementation
Lab Exercises
Authors' Biographies
Index
Blank Page