Digital Signal Processing Using the ARM Cortex M4
Features inexpensive ARM® Cortex®-M4 microcontroller development systems available from Texas Instruments and STMicroelectronics.
This book presents a hands-on approach to teaching Digital Signal Processing (DSP) with real-time examples using the ARM® Cortex®-M4 32-bit microprocessor. Real-time examples using analog input and output signals are provided, giving visible (using an oscilloscope) and audible (using a speaker or headphones) results. Signal generators and/or audio sources, e.g. iPods, can be used to provide experimental input signals. The text also covers the fundamental concepts of digital signal processing such as analog-to-digital and digital-to-analog conversion, FIR and IIR filtering, Fourier transforms, and adaptive filtering.
Digital Signal Processing Using the ARM® Cortex®-M4:
- Uses a large number of simple example programs illustrating DSP concepts in real-time, in an electrical engineering laboratory setting
- Includes examples for both STM32F407 Discovery and the TM4C123 Launchpad, using Keil MDK-ARM, on a companion website
- Example programs for the TM4C123 Launchpad using Code Composer Studio version 6 available on companion website
Digital Signal Processing Using the ARM® Cortex®-M4 serves as a teaching aid for university professors wishing to teach DSP using laboratory experiments, and for students or engineers wishing to study DSP using the inexpensive ARM® Cortex®-M4.
Donald Reay is a lecturer in electrical engineering at Heriot-Watt University in Edinburgh, Scotland. He has also taught hands-on DSP, on a number of occasions, as a visiting lecturer at Zhejiang University in Hangzhou, China. He co-authored Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK, Second Edition (Wiley 2008) with Rulph Chassaing, and is the author of Digital Signal Processing and Applications with the OMAP-L138 eXperimenter (Wiley 2012).
Why Read This Book
You will get a practical, hands-on introduction to implementing DSP algorithms on low-cost ARM Cortex-M4 microcontrollers so you can hear and see real-time results on speakers and oscilloscopes. The book emphasizes applied examples — FIR/IIR filters, FFTs, adaptive filters, and audio/radar/communications demos — that show how to turn DSP theory into working embedded systems.
Who Will Benefit
Undergraduate or graduate engineering students and embedded/software engineers who know DSP fundamentals and want to learn how to implement real-time DSP algorithms on ARM Cortex-M4 hardware.
Level: Intermediate — Prerequisites: Basic calculus and linear algebra, introductory signals & systems (Fourier transform, sampling, filter basics), and familiarity with C programming and microcontroller I/O.
Key Takeaways
- Implement optimized FIR and IIR filters on ARM Cortex-M4 processors using fixed- and floating-point techniques.
- Run real-time FFT-based spectral analysis and visualize results with scope/audio outputs.
- Integrate ADC/DAC and audio I/O on TI and ST development boards to build audible and observable DSP demos.
- Develop and test adaptive filters (e.g., LMS) and apply them to noise cancellation and echo suppression.
- Apply DSP methods to practical domains such as audio/speech processing, radar signal processing, and communications.
- Use Cortex-M4 DSP features (SIMD instructions and single-precision FPU) and common libraries to optimize performance.
Topics Covered
- Introduction to Digital Signal Processing and the ARM Cortex-M4
- Cortex-M4 Development Boards, Toolchains, and Measurement Hardware
- Analog-to-Digital and Digital-to-Analog Conversion, Signal Conditioning
- Discrete-Time Signals, Sampling, and Quantization
- FIR Filter Design and Real-Time Implementation
- IIR Filters and Stability Considerations
- Fast Fourier Transform and Spectral Analysis
- Windowing, Filter Banks, and Practical Spectral Techniques
- Adaptive Filtering and the LMS Algorithm
- Wavelets and Time–Frequency Methods (practical examples)
- Statistical Signal Processing and Noise Analysis
- Applications: Audio/Speech, Radar, and Communications Examples
- Case Studies, Laboratory Experiments, and Project Ideas
- Appendices: CMSIS-DSP overview, C optimization tips, math reference
Languages, Platforms & Tools
How It Compares
Compared with Steven W. Smith's 'The Scientist and Engineer's Guide to DSP', Reay emphasizes embedded, real-time Cortex‑M4 implementation rather than broad intuitive theory; compared with Joseph Yiu's Cortex-M books, Reay focuses on DSP algorithms and applications rather than CPU architecture alone.
