UF0D106 Signal Analysis

Faculty of Philosophy and Science in Opava
Winter 2015
Extent and Intensity
2/0/0. 3 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Stanislav Hledík, Ph.D. (lecturer)
prof. Ing. Jaromír Pištora, CSc. (lecturer)
Guaranteed by
doc. RNDr. Stanislav Hledík, Ph.D.
Centrum interdisciplinárních studií – Faculty of Philosophy and Science in Opava
Prerequisites (in Czech)
UFPA128 Mathematics II
UF/PA128 "Matematika II"
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
Course objectives
The course focuses on digital processing of one-dimensional signals in physics, monitoring technology as wel as in other areas.
Syllabus
  • 1. Basic concepts. Signal continuous, discrete, digital, fields of application, stages of processing, classification of discrete signal processing methods, advantages and disadvantages of discrete and digital signal processing, signals 1D, 2D and multidimensional.
    2. Fourier series (FS) and Fourier transform (FT) continuous signal. Definitions and properties, FT of basic signals, the effect of sampling, convolution and correlation.
    3. Sampling and reconstruction of signal. Ideal and real sampling signal, sampling theorem and alias, reconstructive filter and interpolants.
    4. The Fourier transform of a discrete signal. DTFT, DFT, their inversion and properties.
    5. Discrete unitary transform. Transformation kernel, unitarity, hermiticity, examples: Hadamard, Walsh, DFT, Haar, fast methods of DFT (FFT).
    6. Deterministic and stochastic signals. Stability and causality, linear time-invariant (LTI) systems.
    7. The transfer function, impulse response of the system, bias (in relation to the transmission bandwidth).
    8. Digital filtering and designof digital filters - FIR, IIR (numerical realization of convolution integral, low-pass filter for noise removal, narrowband filters, nonlinear filters, removing cracks).
    9. Wavelet transform (WT). Time-frequency analysis, continuous, discrete WT (CWT / DWT), Daubechies-type DWT, WT implementation by filter banks.
    Current information and additional study materials can be found here: http://www.hledik.org/
Literature
    recommended literature
  • Nevřiva, Pavel. Analýza signálů a soustav. BEN, 2000. ISBN 80-730-0004-0. info
    not specified
  • Jankowski, M. Digital Signal Processing. URL info
  • Prandoni, P., Vetterli, M. Digital Signal Processing. URL info
  • Oppenheim, A. V. MIT OpenCourseWare: Signals and Systems. URL info
Teaching methods
Skills demonstration
Assessment methods
The analysis of student 's performance
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
Teacher's information
Semester exam has oral part only. Knowledge of the nature of discussed methods, supplemented by practical examples, are required. Knowledge of mathematical nature and pictogrammatic approach has precedence over reciting the mathematical formulas (e.g., when discussing the properties of Fourier transform, knowledge of basic transformation pairs and explaination of their properties are required).
The course is also listed under the following terms Summer 1994, Summer 1995, Summer 1996, Summer 1997, Summer 1998, Summer 1999, Summer 2000, Summer 2001, Summer 2002, Summer 2003, Summer 2004, Summer 2005, Summer 2006, Summer 2007, Summer 2008, Summer 2009, Summer 2010, Summer 2011, Summer 2012, Summer 2013, Summer 2014, Winter 2014, Winter 2016, Winter 2017, Winter 2018, Winter 2019, Winter 2020, Winter 2021, Winter 2022.
  • Enrolment Statistics (Winter 2015, recent)
  • Permalink: https://is.slu.cz/course/fpf/winter2015/UF0D106