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.
To develop the ability to DSP systems and create commercially-viable audio applications using high-performance and energy-efficient Arm processors
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 programming 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
Separate purchase of hardware and/or software tools, in order to replicate the course labs
- Discrete-Time Signals and Systems: Convolution and Correlation
- Sampling, Reconstruction and Aliasing: Review of Complex Exponentials and Fourier Analysis
- Sampling, Reconstruction and Aliasing: Time and Frequency Domains
- Time and Frequency Domains: Z-Transform
- FIR Filters: Moving Average Filters
- FIR Filters: Window Method of Design
- IIR Filters: Impulse Invariant and Bilinear Transform Methods of Design
- IIR Filters: Simple Design Example
- Fast Fourier Transform: Review of Fourier Analysis
- Fast Fourier Transform: Derivation of the Radix-2 FFT
- Adaptive Filters: Prediction and System Identification
- Adaptive Filters: Equalization and Noise Cancellation
- Adaptive Filters: Adaptive FIR Filter and the LMS Algorithm
The above syllabus is indicative. It might change from time to time.
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