Digital Signal Processing Online Course

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. You can address that need with this course, which covers basic concepts such as sampling, reconstruction and aliasing, fundamental filtering algorithms such as FIR, IIR and FFT, and software programming basics and principles.

 

 

Course Aim

To develop the ability to DSP systems and create 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

Intellectual

  • 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 programming techniques

Practical

  • 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

Prerequisites

  • Basic C programming and elementary mathematics
  • Separate purchase of hardware and/or software tools, in order to replicate the course labs

 

Syllabus

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: Equalization 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.

 

Access

3 month subscription £70.00

6 month subscription £130.00

12 month subscription £250.00

Lifetime access £499.99

To explore a free module of this course on the Bookshelf platform, click on the Free Preview button below.

Free Preview

Please contact us for more information, trial access, sample materials or to request a quote.

Contact Us