Signals & Systems (ECE_Y425)
Signal Processing (ECE_Y523)
This course offers the basic knowledge in continuous-time and discrete-time signals and systems. This is the prerequisite knowledge for the forthcoming courses as for example communications, signal and image processing, pattern recognition, etc. More specifically, the material covered in this course includes:
Continuous-time Signals and Systems:
- Linear time invariant systems
- Time-domain analysis (convolution)
- Frequency-domain analysis (Fourier transform – Fourier series)
- Frequency response
- Fourier transform in 2 and 3 dimensions
- Hartley transform
- Hilbert transformation
- Signal correlation
Discrete-time Signals and Systems:
- Linear time invariant systems
- Time-domain analysis (convolution)
- Frequency-domain analysis
- Discrete-Time Fourier transform (DTFT)
- Discrete Fourier transform (DFT)
- Fast Fourier Transform (FFT)
- Frequency response
- Z-transform
- Sampling
For lecture slides, bibliography and more visit course’s eclass.
The whole course consists of the following three parts:
Digital Signal Processing:
- Design of digital filters of finite impulse response (FIR) and infinite impulse response (IIR)
- Realisation of digital filters via the fast convolution
- Implementation of digital filters on finite wordlength processors
Information Theory:
- Introduction to information theory (communication model, the measure of information by Shannon)
- Discrete sources of information with or without memory
- Discrete and continuous communication channels
Stochastic Signals:
- First and second moments
- Stationarity and ergodicity
- LTI filtering of stochastic signals
- Spectal estimation
For lecture slides, bibliography and more visit course’s eclass.