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The course provides the fundamental methodologies for the analysis and processing of both deterministic and stochastic signals. |
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Basic knowledge of linear algebra, real and complex analysis, probability and statistics. |
- Introduction.
- Introduction
- Signal classification
- Basic definitions
- Continuous-time deterministic signals and systems
- Fourier analysis:
- Fourier Series and properties
- Continuous-time Fourier Transform and properties
- Linear and time-invariant continuous-time systems:
- Definitions and properties
- The concept of continuous-time convolution
- Impulse response and transfer function
- Stability
- Continuous-time random processes
- Introduction and overview on random variables
- Statistical characterization:
- Probability density functions
- Ensemble averages
- Mean value, standard deviation, variance and autocorrelation
- Wide sense stationary and cyclostationary processes
- Linear filtering of random processes
- Power spectral density
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Βοηθός/Καθηγητή Περιοχή Καθηγητή
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Ο καθηγητής δεν είναι διαθέσιμος
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Λίστα μαγνητοσκοπημένων παραδόσεων |