FPF:UFPFA09 Digital signal analysis and pr - Course Information
UFPFA09 Digital signal analysis and processing
Faculty of Philosophy and Science in OpavaWinter 2019
- Extent and Intensity
- 2/2/0. 6 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. RNDr. Stanislav Hledík, Ph.D. (lecturer)
prof. Ing. Jaromír Pištora, CSc. (lecturer)
doc. RNDr. Stanislav Hledík, Ph.D. (seminar tutor)
Mgr. Adam Hofer (seminar tutor) - Guaranteed by
- doc. RNDr. Stanislav Hledík, Ph.D.
Centrum interdisciplinárních studií – Faculty of Philosophy and Science in Opava - Prerequisites (in Czech)
- TYP_STUDIA ( N )
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Computational Physics (programme FPF, N1701 Fyz)
- Course objectives
- The course focuses on digital processing and analysis of one-dimensional signals in the natural sciences, especially in physics and in measuring and monitoring technology. The lectures are supplemented by practical demonstrations and interactive demonstrations using Mathematica.
- Syllabus
- Introduction. Basic concepts, systems and signals in continuous and discrete time. Properties and classification of discrete and digital signal processing, time and amplitude discretization, stage of processing and application areas.
Discrete Signals and Systems. Sampling and reconstruction, the sampling theorem. Z -transform, discrete linear systems.
Discrete linear transformations. Development of periodic functions in the harmonic series, Fourier series and their properties. The continuous Fourier transform and its properties. General discrete unitary transformation, discrete Fourier transform ( DFT) and its fast calculation method (FFT ). Cosine and sine transformation. Convolution and deconvolution, correlation and autocorrelation using DFT. Wavelet transform continuous and discrete filter banks.
Random signals and processes. Correlation and covariance functions, stationary and ergodic processes, spectra, and relative power spectrum. Transmission of random signal linear system.
Spectral analysis. Spectral analysis of deterministic, periodic, and general stochastic signals. Time-frequency analysis. Estimation of power spectra. Mutual spectrum.
Correlation analysis. Properties of correlation, covariance, autocorrelation and autocovariance functions. Methods of estimating correlation functions. Correlation analysis of the signal.
Linear signal filtering. Principles of digital filtering. FIR and IIR filters. Convolution, convolution theorem, filtering in the frequency domain. Types of filters.
Nonlinear and adaptive signal filtering. Nonlinear discrete dynamical systems, general and polynomial nonlinear discrete systems, filters based on sorting, filtering homomorfická. Power cepstrum. Nonlinear matched filters. Adaptive filters, the types and applications, a linear adaptive prediction, adaptive interference suppression.
Restaurant signal. Model bias, and the pseudoinverse deconvolution. Wiener filtering, Kalman filtering. Anti-aliasing ( smoothing ) of data. Deconvolution to optimize the shape of the impulse response. The method of entropy maximization.
Detection of small signals in noise. The correlation properties of the useful signal and noise. Finding known phenomena in which the signal is correlated. Correlation and autocorrelation method, its use ( Radar, reflectometry), practical methods of calculating the autocorrelation function.
Signal compression. Lossless compression, medium level of information, entropy, predictive coding, delta - coding, entropy coding, basic computer lossless compression formats. Lossy compression, redundant components, properties recipient signal components from the transformed signal subband coding, masking, basic computer lossy compression formats.
- Introduction. Basic concepts, systems and signals in continuous and discrete time. Properties and classification of discrete and digital signal processing, time and amplitude discretization, stage of processing and application areas.
- Literature
- Language of instruction
- English
- Further comments (probably available only in Czech)
- The course can also be completed outside the examination period.
- Teacher's information
- The attendance at lectures is recommended. It can be substituted by the self-study of recommended literature and individual consultations. Tutorial attendance is compulsory (min. 80%).
- Enrolment Statistics (Winter 2019, recent)
- Permalink: https://is.slu.cz/course/fpf/winter2019/UFPFA09