Welcome to our Digital Signal Processing Education Kit!

Our flagship offering to universities worldwide is the Arm University Program Education Kit series.

These self-contained educational materials offered exclusively and at no cost to academics and teaching staff worldwide. They’re designed to support your day-to-day teaching on core electronic engineering and computer science subjects. You have the freedom to choose which modules to teach – you can use all the modules in the Education Kit or only those that are most appropriate to your teaching outcomes.

Our Digital Signal Processing Education Kit covers the fundamental theory and practice of managing digital signals. A full description of the education kit can be found here.

• A full set of lecture slides, ready for use in a typical 10-12-week undergraduate course (full syllabus below).
• Lab manual with solutions for faculty. Labs are based on low-cost hardware platforms (donated by partners and subject to availability) powered by Arm Cortex-M-based microcontrollers that enable high performance yet energy-efficient digital signal processing, and use the industry-standard Keil MDK-Arm application development tool.
• Prerequisites: Basic C programming, elementary mathematics.

To develop the ability to implement DSP systems and create commercially viable audio applications using high performance and energy-efficient Arm processors.

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. Z-Transform: Time and Frequency Domains
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 Transformation
10. Fast Fourier Transform: Derivation of Radix-2 FFT
11. Adaptive Filters: Prediction and System Identification
12. Adaptive Filters: Equalization and Noise Cancellation
13. Adaptive Filters: Adaptive FIR Filter

See uni-adapted branch here which is where we list standalone GitHub repositories of teaching material adapted and modified by academics from various universities

You are free to fork or clone this material. See LICENSE.md for the complete license.

Arm is committed to making the language we use inclusive, meaningful, and respectful. Our goal is to remove and replace non-inclusive language from our vocabulary to reflect our values and represent our global ecosystem.

Arm is working actively with our partners, standards bodies, and the wider ecosystem to adopt a consistent approach to the use of inclusive language and to eradicate and replace offensive terms. We recognise that this will take time. This course may contain references to non-inclusive language; it will be updated with newer terms as those terms are agreed and ratified with the wider community.

Contact us at [email protected] with questions or comments about this course. You can also report non-inclusive and offensive terminology usage in Arm content at [email protected].