440-2107/01 – Signal Processing Methods in Communication Technologies (ZSK)
Gurantor department | Department of Telecommunications | Credits | 4 |
Subject guarantor | Ing. Jan Skapa, Ph.D. | Subject version guarantor | Ing. Jan Skapa, Ph.D. |
Study level | undergraduate or graduate | Requirement | Choice-compulsory type A |
Year | 2 | Semester | summer |
| | Study language | Czech |
Year of introduction | 2019/2020 | Year of cancellation | 2024/2025 |
Intended for the faculties | FEI | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
The aim of the course is to teach students the basic methods and principles of 1D, 2D and multidimensional signal processing in their analysis and transmission by communication transmission chain. Attention is paid to both model (artificial) and real signal (speech signals, real images). Students will learn what tools can be used to analyze and process single and multidimensional signals. They will learn, how to compare those tools to each other in terms of their usability in specific applications. Then, students will be able to apply these tools in a specific case, critically evaluate, analyze and present the results.
Teaching methods
Lectures
Individual consultations
Tutorials
Experimental work in labs
Project work
Summary
The course focuses on fundamental principles and methods of signal processing during its transmission through the communication chain. Students will learn the concepts of frequency, spectrum of signal and their meanings.
Furthermore, they will learn basic signal transforms and their influence on the spectrum. They will learn the meaning of Fourier series, Fourier transform, window functions and Short-time Fourier transform. They will learn the principles of 1D and 2D signals sampling and phenomena that occur during sampling (aliasing, leakage, moiré). They will learn the principles of 1D and 2D discrete Fourier transform and Discrete cosine transform. Furthermore, students will learn two-dimensional Fourier transform and its importance for optical imaging in optical communications. At the end of the course students will be introduced to the concept of kepstrum and its use in applications of speech signal processing (speech to text), speaker recognition, text to speech.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
2 tests
2 projects
Oral exam and written test
E-learning
Other requirements
No additional requirements.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Communication transmission chain.
Basic types of signals.
Spectrum of basic types of signal.
Fourier series, Fourier transform.
Basic signal transformations and their influence on spectrum.
Window functions and their spectral properties. Short time Fourier transform. Spectrogram.
1D and 2D ideal sampling function. Sampling theorem.
Reconstruction of signals using ideal lowpass filter.
1D and 2D discrete Fourier transform, discrete cosine transform and their comparison.
Filtration and its influence on signal spectrum. Speech band.
2D discrete Fourier transform and its relation to optical systems. Airy disc.
Cepstrum and its use in speech signal processing.
Fundamentals of speech signal processing (speech to text, speaker recognition, text to speech).
Multidimensional signals, their analysis and transmission.
Students will proceed from everyday's experience through mathematical modeling to simulations.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction