352-0507/02 – Signal Processing (ZprS)
| Gurantor department | Department of Control Systems and Instrumentation | Credits | 3 |
| Subject guarantor | doc. Ing. Renata Wagnerová, Ph.D. | Subject version guarantor | prof. Ing. Jiří Tůma, CSc. |
| Study level | undergraduate or graduate | Requirement | Choice-compulsory |
| Year | 1 | Semester | summer |
| | Study language | Czech |
| Year of introduction | 2004/2005 | Year of cancellation | 2009/2010 |
| Intended for the faculties | FS | Intended for study types | Master |
Subject aims expressed by acquired skills and competences
The aim of the lectures on signal processing is to give students basic knowledge of the theory of digital filters, Fourier and wavelet transform, FFT techniques, spectral and correlation analysis, evaluation autospekter, cross-spectrum and frequency characteristics. The lecture describes the evaluation methods of frequency spectra of deterministic and stochastic signals, the method of selecting the time window, overlapping blocks of averaging and spectral averaging alone. Theoretical lectures are combined with demonstrations of examples of the measured signals and evaluating the possibilities of using theory in practice. Understanding the methods used in signal processing to analysis and measurement applications, design of computer applications for data processing (filtering and frequency analysis). The aim is to reach independent decisions and evaluate the measured data and the method of their processing.
Teaching methods
Lectures
Individual consultations
Tutorials
Experimental work in labs
Project work
Summary
Filtering (analogue and digital filters – FIR and IIR filter design), sampling (Shannon theorem), signal taxonomy (deterministic and stochastic signals), analysis of signals in the time and frequency domain, Fourier transform (FFT, DIT, DIF, butterfly algorithms), frequency spectra (time window, overlay, averaging in the time domain), frequency response (noise and impulse responses), synchronous averaging in the time domain, analytical signal (Hilbert transform), envelope analysis, phase demodulation, tracking filters, signal resampling.
Compulsory literature:
Recommended literature:
Tůma, J. Signal Analyser, software supporting lectures on signal processing. Ostrava: VŠB-TU Ostrava, 20002-2004. (free download).
Way of continuous check of knowledge in the course of semester
E-learning
Other requirements
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Nature of signals. Sampling, sampling frequency. Analog and digital filters, digital filters derived from analog filters, bilinear transform.
2. First-order filter and notch filter. FIR and IIR filters. Comparison of the filter properties, the proposal for design in Matlab.
3. Fourier transform (FT). Dictionary, transform of integration and differentiation operations. Autospektrum graduated RMS, PWR, and PSD.
4. FT of constant and harmonic signals. Effect of the time window on the frequency spectrum
5. Methods for calculating the fast Fourier transform (FFT). DIT and DIF method, butterfly diagrams. Speeding up the calculation.
6. Calculation spectra by overlapping blocks for the averaging spectra.
7. Hilbert transform. Analytical signal. Envelope and phase analytical signal. Amplitude and phase modulation and demodulation.
8. Resampling the signal. Order analysis.
9. Synchronous filtering signals. Frequency response of synchronous filtering.
10. Measurement of frequency response using the Fourier transform. Test signal like impulse and white noise.
11. Coherence and factors affecting the accuracy of frequency responses (resonance, antiresonance, linearity and unmeasured inputs)
12. Wavelet transform. Continuous and discrete. The use of wavelets for noise removal, signal compression and indication of breakpoint
13. Vold-Kalman order filtration. Data and structural equations. Global solutions. The use of the VK filter for research quality sound systems
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.