Module Specifications..
Current Academic Year 2023 - 2024
Please note that this information is subject to change.
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Repeat examination Array |
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Description The overarching objective of the module is to develop in the participants practical time-invariant 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, non-linear 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 Z-Transforms 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 |
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Indicative Content and Learning Activities
Indicative Syllabus1. 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 Z-transform and its applications in DSP, 7. Non-recursive (Finite Impulse Response) and recursive (Infinite Impulse Responses) filter design, 8. The Fast Fourier Transform (FFT) and its applications in DSP.1. Signal SamplingShannon's theorem, Nyquist concepts, etc.,2. NoiseSources and statistics of noise3. Linear systemsLinear DSP systems: Scope, definitions and concepts,4. Time domainAnalysing DSP system in the time domain: responses, etc.,5. Frequency domainAnalysing DSP system in the frequency domain:Discrete Fourier Series (DFS) and Discrete Fourier Transform (DFT),6. Z-transformThe Z-transform and its applications in DSP,7. Filter designNon-recursive (Finite Impulse Response) and recursive (Infinite Impulse Responses) filter design,8. FFTThe Fast Fourier Transform (FFT) and its applications in DSP. | |||||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||||
Programme or List of Programmes
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Date of Last Revision | 16-AUG-05 | ||||||||||||||||||||||||||||||||||||||
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