Module Specifications..
Current Academic Year 2023  2024
Please note that this information is subject to change.
 
Repeat examination Array 

Description The overarching objective of the module is to develop in the participants practical timeinvariant digital signal system design skills. The module focusses on prototypical linear time invariant systems and aims to be the stepping off point for more advanced modules in adaptive, nonlinear and time varying systems.  
Learning Outcomes 1. Describe the fundamental properties of linear time invariant systems 2. State, prove and apply Shannon's sampling theorem 3. Relate signal to noise ratio (SNR) to number of samples averaged in signal sampling and averaging systems 4. Compute the impulse response of DSP systems and combine it with convolution techniques to compute DSP system response for any arbitrary input (and vice versa). 5. Write down, state the properties of, and apply Fourier Transforms and ZTransforms in DSP systems 6. Design, obtain the properties of and code basic window (or apodization) functions 7. Design basic finite impulse response (FIR) and infinite impulse response (IIR) filters  
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml 

Indicative Content and Learning Activities
Indicative Syllabus 1. Signal Sampling: Shannon's theorem, Nyquist concepts, etc., 2. Noise: Sources and Statistics, 3. Linear DSP systems:Scope, definitions and concepts, 4. Analysing DSP system in the time domain: responses, etc., 5. Analysing DSP system in the frequency domain:Discrete Fourier Series (DFS) and Discrete Fourier Transform (DFT), 6. The Ztransform and its applications in DSP, 7. Nonrecursive (Finite Impulse Response) and recursive (Infinite Impulse Responses) filter design, 8. The Fast Fourier Transform (FFT) and its applications in DSP. 1. Signal Sampling Shannon's theorem, Nyquist concepts, etc., 2. Noise Sources and statistics of noise 3. Linear systems Linear DSP systems: Scope, definitions and concepts, 4. Time domain Analysing DSP system in the time domain: responses, etc., 5. Frequency domain Analysing DSP system in the frequency domain:Discrete Fourier Series (DFS) and Discrete Fourier Transform (DFT), 6. Ztransform The Ztransform and its applications in DSP, 7. Filter design Nonrecursive (Finite Impulse Response) and recursive (Infinite Impulse Responses) filter design, 8. FFT The Fast Fourier Transform (FFT) and its applications in DSP.  
 
Indicative Reading List
 
Other Resources None  
Programme or List of Programmes
 
Date of Last Revision  16AUG05  
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