Lists
ListsSummary
Description:
Our Digital Signal Processing Education Kit covers the fundamental theory and practice of managing digital signals.
Organisations: Arm Education
Target Audience
University students studying in computer science, electronic engineering or other engineering related degrees. Hobbyists, early-career professionals. Makers. Lecturers.
Learning Aims:
Knowledge and understanding of
- The properties of discrete-time linear time-invariant system, including how convolution and correlation works.
- The properties of a Finite Impulse Filter (FIR) and identify its relationship with a moving average filter.
- The properties of an Infinite Impulse Response (IIR) filter, and compare the bilinear transform and impulse invariant methods for IIR filter design.
- How to design the mathematical elements of a simple FIR filter using the impulse invariant and bilinear transform methods.
- The various types of Fourier analyses and their application.
- The operations of a Finite Impulse Filter (FIR) filter as a basis of a linear adaptive filter, including cost functions, Steepest Descent, and Least Means Squares (LMS) algorithms.
Intellectual
- Describe the Fourier Transform properties of various types of signals.
- Explain how sampled and reconstructed signals in a basic signal processing system are represented by using Fourier-Transform and Nyquist theorem.
- Describe the definition, properties, and usage of the z-transform for signal analyses.
- Explain how to design basic low-pass and high-pass FIR filters using the window method.
- Explain how the Radix-2 decimation algorithm works for calculating Fast Fourier Transform (FFT).
- Describe the operation of adaptive systems including prediction and system identification configurations.
- Describe the operation of the equalization and noise cancellation configuration involving adaptive filters.
Practical
- Demonstrate the successful set up of hardware and software requirements for digital signal processing concepts and projects.
- Examine the effects of signal sampling, reconstruction, and aliasing using an audio codec and Digital-to-Analog Converter (DAC) on a development board.
- Design and implement a Finite Impulse Response (FIR) and an Infinite Impulse Response (IIR) filter for digital signal processing.
- Use an Arm-based development board and Integrated Development Environment (IDE) in example projects related to basic DSP concepts.
- Use and assess Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT) for real-time signal processing.
- Implement and use adaptive filters using the Least Mean Squares (LMS) algorithm for digital signal processing applications.
Resources
Loading previews...|
README.md
Text
|
View metadata | Download |
![[thumbnail of README.md]](https://compedulabs.org/style/images/fileicons/text.png)
README.md
![[thumbnail of ConvolutionAndCorrelation_lec.pptx]](https://compedulabs.org/style/images/fileicons/slideshow.png)
Module 1: Discrete-Time Signals and Systems - Convolution and Correlation
Module 1: Discrete-Time Signals and Systems - Convolution and Correlation, Module 1, Lab Manual
![[thumbnail of Module 1: Lab 0 Getting Started]](https://compedulabs.org/style/images/fileicons/unknown.png)
Module 1: Lab 0 Getting Started
Module 1: Lab 01 Analog IO
Module 2: Sampling, Reconstruction and Aliasing - Review of Complex Exponentials and Fourier Analysis
Module 3: Sampling, Reconstruction and Aliasing - Time and Frequency Domains
Module 3: Sampling, Reconstruction and Aliasing - Time and Frequency Domains: Lab Manual
Module 3: Lab 02 Sampling Aliasing and Reconstruction
Module 4: Time and Frequency Domains - z-transform
Module 5: FIR Filters - Moving Average Filters
Module 6: FIR Filters - Window Method of Design
Module 6: FIR Filters - Window Method of Design: Lab Manual
Module 6: Lab 03 FIR Filters
Module 7: IIR Filters - Impulse Invariant and Bilinear Transform Methods of Design
Module 8: IIR Filters - Simple IIR Filter Design Example
Module 8: IIR Filters - Simple IIR Filter Design Example: Lab Manual
Module 8: Lab 04 IIR Filters
Module 9: Fast Fourier Transform - Review of Fourier Analysis
Module 10: Fast Fourier Transform - Derivation of Radix-2 FFT
Module 10: Fast Fourier Transform - Derivation of Radix-2 FFT: Lab Manual
Module 10: Lab 05 Fast Fourier Transform
Module 11: Adaptive Filters - Prediction and System Identification
Module 12: Adaptive Filters - Equalisation and Noise Cancellation
Module 13: Adaptive Filters - Adaptive FIR Filter and the LMS Algorithm
Module 13: Adaptive Filters - Adaptive FIR Filter and the LMS Algorithm: Lab Manual
Module 13: Lab 06 Adaptive Filters
Details
Our Digital Signal Processing Education Kit covers the fundamental theory and practice of managing digital signals.
Course Type: Open
People
Organisations: Arm Education
| Contributors: | GitHub Contributor: | Liz Warman |
|---|---|---|
| GitHub Contributor: | David Mackenzie | |
| GitHub Contributor: | Oyinkuro Benafa | |
| GitHub Contributor: | Francis Catan | |
| GitHub Contributor: | Mark Allen | |
| GitHub Contributor: |
Certification
Course Structure
Taxonomy
Subjects: Technology > Tools & Models > Arm DS-Gold
Interests: Analogue Digital Converter (ADC) , Discrete time signal , Digital Signal Processing (DSP)
Other
Course URL: https://github.com/arm-university/Digital-Signal-Processing-Education-Kit
Metadata
Discussion