Course detail
Data acquisition,analysis and processing.
FEKT-MZPDAcad. year: 2012/2013
Data sequence, analysis and transformation.Discrette Convolution, Deconvolution, Correlation. Ortogonal transformation, analysys and calculating DFT. Interpolation, derivatin and integration. Trend removal methods. Numeric parameters and histograms. Spectral, Correlation and Ceptral analysis. Compression. Filtration. Indentification of linear systems.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
70 points - final test
Course curriculum
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
Display time series data. Basic work on time series. Discrette convolutin.
Discrette corelation. Discrette deconvolution.
Discrette ortogonal transform. DFT, characteristics.
Principle of FFT, other discrette ortogonal transform.
Preprocessing time series data. Derivation and integration.
Trend removal.Numeric parameters and histograms.
Spectral, Correlation and Cepstral analysis.
Interpolation problem.
Compression.
Filtration.
Designing digital filter methods.
Indentification of linear systems.
Exercise in computer lab
Teacher / Lecturer
Syllabus
Simple data display system.
Generation time series. Sorting, Data operation speed.
Individual work.
Discrette convolution and corelation.
DFT comparation.
Discrette Haar transform. Time window.
Individual work
Amplitude, phase and power spectrum.
Regress analze.
Interpolation in time series data.
Histograms. Digital filters.
Finish.