Digital Signal Processing Education Kit

Course Aim

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

Learning Outcomes

• 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. 

Syllabus