Digital Signal Processing

The explosion of digital data in today’s world means it is crucial for learners to understand and practice how to manage and process digital signals that come in from a wide variety of sources. Arm Education Media is addressing this need with the creation of our Digital Signal Processing (DSP) online course.

This online course is powered by Arm Cortex-M4-based microcontrollers, which enable high performance yet energy-efficient digital signal processing at a very affordable price. By reducing the barrier of entry  with the introduction of these low cost development boards, the DSP online course will allow students to practice theory with advanced hardware.

If you are interested in an institutional subscription, contact the Arm Education Media team at

Course aims

The course aims to help learners develop their capability of designing DSP systems and creating commercially-viable audio applications using high-performance and energy-efficient Arm processors.

Learning outcomes

Knowledge and understanding of

  • DSP basic concepts such as sampling, reconstruction and aliasing
  • Fundamental filtering algorithms such as FIR, IIR, FFT
  • Arm-based microcontrollers as low-power DSP computing platforms
  • Software programming basics and principles


  • Ability to choose between different DSP algorithms for different applications
  • Ability to use different design methods to achieve better results
  • Ability to evaluate experimental results (e.g. quality, speed, power) and correlate them with the corresponding designing and programing techniques


  • Ability to implement DSP algorithms and design methods on Arm-based microcontrollers
  • Ability to use commercial hardware and software tools to develop real time DSP application


Basic C programming and Elementary mathematics


The hardware used in this course include:

  • Cypress FM4 development board

The hardware bundle can be purchased at Digi-Key Electronics

Course syllabus

Module name
1. Discrete-Time Signals and Systems: Convolution and Correlation
2. Sampling, Reconstruction and Aliasing: Review of Complex Exponentials and Fourier Analysis
3. Sampling, Reconstruction and Aliasing: Time and Frequency Domains
4. Time and Frequency Domains: Z-Transform
5. FIR Filters: Moving Average Filters
6. FIR Filters: Window Method of Design
7. IIR Filters: Impulse Invariant and Bilinear Transform Methods of Design
8. IIR Filters: Simple Design Example
9. Fast Fourier Transform: Review of Fourier Analysis
10. Fast Fourier Transform: Derivation of the Radix-2 FFT
11. Adaptive Filters: Prediction and System Identification
12. Adaptive Filters: Equalisation and Noise Cancellation
13. Adaptive Filters: Adaptive FIR Filter and the LMS Algorithm

The above syllabus is indicative. It might change from time to time.