Combined study

4 years

prof. Ing. Zdeněk Smékal, CSc.

Chairman :
prof. Ing. Zdeněk Smékal, CSc.
Councillor internal :
doc. Ing. Radim Burget, Ph.D.
prof. Ing. Jiří Mišurec, CSc.
doc. Ing. Vladislav Škorpil, CSc.
doc. Ing. Jiří Hošek, Ph.D.
prof. Ing. Jaroslav Koton, Ph.D.
Councillor external :
doc. Ing. Otto Dostál, CSc.
prof. Ing. Boris Šimák, CSc.
prof. Ing. Ivan Baroňák, Ph.D.

The student is fostered to use the theoretical knowledge and experience gained through own research activities in an innovative manner. He is able to efficiently use the gathered knowledge for the design of own and prospective solutions within their further experimental development and applied research. The emphasis is put on gaining both theoretical and practical skill, ability of self-decisions, definition of research and development hypotheses to propose projects spanning from basic to applied research, ability to evaluation of the results and their dissemination as research papers and presentation in front of the research community.

The doctor study program "Teleinformatics" aims to generate top research and development specialists, who have deep knowledge of principles and techniques used in communication and data wired and wireless networks and also in related areas and also in data/signal acquisition, processing and the back representation of user data on the level of application layer. The main parts of the studies are represented by areas dealing with information theory and communication techniques. The graduate has deep knowledge in communication and information technologies, data transfer and their security. The graduate is skilled in operation systems, computer languages and database systems, their usage and also design of suitable software and user applications. The graduate is able to propose new technology solution of communication tools and information systems for advanced transfer of information.

Graduates of the program "Teleinformatics" apply in particular in research, development and design teams, in the field of professional activity in production or business organizations, in the academic sphere and in other institutions involved in science, research, development and innovation, in all areas of the company where communication systems and information transfer through data networks are being applied and used.
Our graduates are particularly experienced in the analysis, design, creation or management of complex systems aimed for data transfer and processing, as well as in the programming, integration, support, maintenance or sale of these systems.

Doctoral studies are carried out according to the individual study plan, which will prepare the doctoral student in cooperation with the doctoral student at the beginning of the study. The individual study plan specifies all the duties stipulated in accordance with the BUT Study and Examination Rules, which the doctoral student must fulfill to successfully finish his studies. These responsibilities are time-bound throughout the study period, they are scored and fixed at fixed deadlines. The student enrolls and performs tests of compulsory courses, at least two obligatory elective subjects with regard to the focus of his dissertation, and at least two elective courses (English for PhD students, Solutions for Innovative Entries, Scientific Publishing from A to Z).
The student may enroll for the state doctoral exam only after all the tests prescribed by his / her individual study plan have been completed. Before the state doctoral exam, the student prepares a dissertation thesis describing in detail the goals of the thesis, a thorough evaluation of the state of knowledge in the area of ​​the dissertation solved, or the characteristics of the methods it intends to apply in the solution. The defense of the controversy that is opposed is part of the state doctoral exam. In the next part of the exam the student must demonstrate deep theoretical and practical knowledge in the field of microelectronics, electrotechnology, materials physics, nanotechnology, electrical engineering, electronics, circuit theory. The State Doctoral Examination is in oral form and, in addition to the discussion on the dissertation thesis, it also consists of thematic areas related to compulsory and compulsory elective subjects.
To defend the dissertation, the student reports after the state doctoral examination and after fulfilling conditions for termination, such as participation in teaching, scientific and professional activity (creative activity) and at least a monthly study or work placement at a foreign institution or participation in an international creative project .

The doctoral studies of a student follow the Individual Study Plan (ISP), which is defined by the supervisor and the student at the beginning of the study period. The ISP is obligatory for the student, and specifies all duties being consistent with the Study and Examination Rules of BUT, which the student must successfully fulfill by the end of the study period. The duties are distributed throughout the whole study period, scored by credits/points and checked in defined dates. The current point evaluation of all activities of the student is summarized in the “Total point rating of doctoral student” document and is part of the ISP. At the beginning of the next study year the supervisor highlights eventual changes in ISP. By October, 15 of each study year the student submits the printed and signed ISP to Science Department of the faculty to check and archive.
Within the first four semesters the student passes the exams of compulsory, optional-specialized and/or optional-general courses to fulfill the score limit in Study area, and concurrently the student significantly deals with the study and analysis of the knowledge specific for the field defined by the dissertation thesis theme and also continuously deals with publishing these observations and own results. In the follow-up semesters the student focuses already more to the research and development that is linked to the dissertation thesis topic and to publishing the reached results and compilation of the dissertation thesis.
By the end of the second year of studies the student passes the Doctor State Exam, where the student proves the wide overview and deep knowledge in the field linked to the dissertation thesis topic. The student must apply for this exam by April, 30 in the second year of studies. Before the Doctor State Exam the student must successfully pass the exam from English language course.
In the third and fourth year of studies the student deals with the required research activities, publishes the reached results and compiles the dissertation thesis. As part of the study duties is also completing a study period at an abroad institution or participation on an international research project with results being published or presented in abroad or another form of direct participation of the student on an international cooperation activity, which must be proved by the date of submitting the dissertation thesis.
By the end of the winter term in the fourth year of study students submit the elaborated dissertation thesis to the supervisor, who scores this elaborate. The final dissertation thesis is expected to be submitted by the student by the end of the fourth year of studies.
In full-time study form, during the study period the student is obliged to pass a pedagogical practice, i.e. participate in the education process. The participation of the student in the pedagogical activities is part of his/her research preparations. By the pedagogical practice the student gains experience in passing the knowledge and improves the presentation skills. The pedagogical practice load (exercises, laboratories, project supervision etc.) of the student is specified by the head of the department based on the agreement with the student’s supervisor. The duty of pedagogical practice does not apply to students-payers and combined study program students. The involvement of the student in the education process within the pedagogical practice is confirmed by the supervisor in the Information System of the university.

1. Analog circuits containing elements with the fractional order

   The thesis is focused on modeling, simulations and experimental verification of structures where relation between response and driving signal contains derivation or integration of non-integer order (so-called fractional structures or circuits). The task is also to design of suitable application possibilities of fractional order circuits, e.g. frequency filters, reconfigurable filters, tunable oscillators or other circuits. Attention should be kept also on other ways how to implement fractional order circuits, e.g. implementation of structures with distributed parameters (RC-EDP), on computer modelling of matter and structures from nature and biology and also on mathematical description.

   Tutor: Jeřábek Jan, doc. Ing., Ph.D.

2. Automatic music transcription of recordings into symbolic representation

   Automatic Music Transcription (AMT) is a branch of the Music Information Retrieval (MIR) discipline that combines the creation of logical music structures, perception (music analysis), recognition of musical objects and digital signal processing. AMT focuses on the development of algorithms that change the representation of a music signal (in the form of digital recordings) into a form of symbolic notation (score) and includes several other specific algorithms such as multi-pitch estimation, or rhythm and beat detection. Recently, however, the implementation of artificial neural networks and machine learning methods has prevailed. The use of these methods is tied to many tools – from notation systems, music studios to analytical software for musicological research. This thesis aims to create a system and improve the current methods of automatic music transcription to symbolic notation.

   Tutor: Smékal Zdeněk, prof. Ing., CSc.

3. Design of Modern IP Sophisticated Telematics Systems in Transport

   Telematics systems are particularly common in transport. Research into telematics systems based on the Internet Protocol will be focused on the design of sophisticated, i.e. well-defined, formally well-developed and complicated methods that use IP systems in various areas. Surveillance and protection systems, systems of paying the fare, information systems, interactive applications, etc. are supposed in particular. Localization by GPS, vehicle diagnostics, and vehicle monitoring on orthomaps in real situations are in the focus. Sophisticated telematics systems will be software simulated, optimized and subsequently hardware implemented in the form of functional prototypes. Communication between two cars without a driver intervention, collision avoidance, information transmission about traffic from the places that cars left are expected. A highly accurate navigation system based on the Galileo system (GNSS) for controlling functional blocks of cars is considered.

   Tutor: Škorpil Vladislav, doc. Ing., CSc.

4. Development of Algorithms for Management of Queues and Control of Switching in Active Network Elements

   Today's active network elements use a range of powerful algorithms for management of queues and control of switching. The task is to implement selected algorithms of queues management into a development system equipped with the FPGA card, to measure their performance and to develop a custom algorithm of queues management while respecting the standard marking used for QoS solutions. The solution assumes knowledge of languages C, VHDL, MATLAB, and possibly Verilog. An architecture of a network element with priority routing will be designed. An original procedure will be proposed for modelling this problem mathematically together with the implementation of the mathematical model. Software simulation of a system that can be used to control the switching field designed for switching data units shall be extended by its hardware implementation, e.g. via programmable logical arrays of the development system FPGA. The knowledge obtained will be generalized and related to the theory of high-speed network elements.

   Tutor: Škorpil Vladislav, doc. Ing., CSc.

5. Effective Use of IP Networks in Crisis Situations

   The aim is to create an effective strategy for the use of the public and private IP networks for crisis management. Also to propose such a network, which could have the capacity, but also in terms of resistance, to guarantee the crisis communication. This would be in particular traffic data, voice, and e.g. to manage the flow of information, etc. Research should also include the influence of network topology on its stability and security, the speed of the spread of viruses, ability to resist attacks, etc. One of the objectives is to design a software robot that will be able to monitor the network, and TV broadcasting. Other parts would propose new methods of Internet communication management, where appropriate, the Internet topology. The aim is to design a system for exchanging files over the Internet, but without any central control. The system should be intuitively usable. The solution should be safe and allow anonymity of the sender and the recipient of the data. The final objective is a theoretically supported design of a highly durable network suitable for crisis situations.

   Tutor: Škorpil Vladislav, doc. Ing., CSc.

6. Methods for measurement of basic and derived parameters of data networks

   Goal of this thesis is to research in area of measurement of basic parameters of data networks based mostly on Internet Protocol (IP), such as throughput, one-way delay and round-trip time, so as in area of derived parameters, such as quality of voice and video services. This comes with problematics of modelling of behaviour of network and user under various conditions, long-term and short-term events, a description of mass-serving systems and also features and behaviour key internet and measuring protocols in computer networks, so as topic of their possible setting and security. Based on analysis of available tools and their features, or development of own tools, design of solution and approaches for various types of measurements is expected. Designed methodology should be verified both in environment of lab and real-world networks.

   Tutor: Jeřábek Jan, doc. Ing., Ph.D.

7. Musical source separation using machine learning and ANN techniques

   Digital music signal processing and Music Information Retrieval (MIR) is a rapidly growing multidisciplinary scientific field. Separation of the music source is one of the unresolved and desired topics – the most promising results so far have been shown by techniques based on machine learning, and especially on artificial neural networks. Ideally, this system separates individual instruments from the final mixed music recording to create tracks that were separated before mixing and post-processing. The advantage is possible manipulation of recordings as if we had access to separate channels. The increasing accuracy of the methods enhances the possibility of use in automatic transcription of music recordings to musical notation, in analytical software, or the processing of sound recordings in recording studios. This thesis aims to create a system and improve the current methods for automatic separation of music sources.

   Tutor: Smékal Zdeněk, prof. Ing., CSc.

8. Parallelization of Genetic Algorithms

   The aim is research in the field of genetic algorithms parallelization. Parallelization is an integral part of an endeavour to increase effectiveness of genetic algorithms and their possible use. Research should build on current knowledge and carry out further research on the impact of selected parameters and design details on the performance. According to the chosen method the knowledge of some programming language is required, as well as scripting languages Python or Matlab. Selected development and testing environment is left to free choice. The results should be presented and verified.

   Tutor: Škorpil Vladislav, doc. Ing., CSc.

9. Spatial Audio Signal Processing Using Small-Size Microphone Arrays

   Microphone arrays of small dimensions, mainly fitted with MEMS microphones, are currently used in a number of applications, such as voice assistants, robots or monitoring in sensor networks, especially for their ability of spatial filtering of the sound signal from background noise. However, they also have potential in multimedia applications including augmented and virtual reality. The problem, however, is the limitation of their dimensions with respect to the spatial filtering capability at low sampling frequencies. The aim of this dissertation is to use new methods of spatial filtering of sound signal picked up by a field of microphones in order to further reduce the dimensions of the field and increase the resolution and accuracy of filtering. The dissertation will focus not only on the research for suitable algorithms of signal processing, but also on its mechanical design enabling the adjustment of acoustic properties of microphones, especially the shaping of directional characteristics. The research will be carried out in cooperation with the Faculty of Transportation Sciences of the Czech Technical University and the Université du Maine Le Mans.

   Tutor: Schimmel Jiří, doc. Ing., Ph.D.

10. Using Machine Learning for Modelling of Audio Systems

    Neural networks and machine learning are currently used in the area of audio signal processing for data mining, e.g. recognition of genre, music information retrieval from recordings, etc., and speech processing, such as word recognition, speaker identification, emotion recognition, etc. However, their potential use is also in modelling of audio systems. The aim of dissertation thesis is to find algorithms for optimization of parameters of digital musical effects, algorithms for room acoustic simulation and more using machine learning and hearing models for training of neural networks. The research will focus on the static optimization of the system parameters according to the original analog system and on the dynamic change of the parameters in real time on the basis of the properties of the processed audio signal. Research will be conducted in collaboration with companies dealing with the development of software for processing audio signals.

    Tutor: Schimmel Jiří, doc. Ing., Ph.D.

1. round (applications submitted from 01.04.2022 to 15.05.2022)

1. Clinically interpretable machine learning in the field of predictive analysis of neurodegenerative and neurodevelopmental disorders

   As the population ages, there is an increasing demand for computerized analysis of data acquired from patients suffering from neurodegenerative or neurodevelopmental diseases in order to provide objective diagnosis, assessment, treatment, and prevention of these diseases. The aim of this dissertation thesis is to research and develop multimodal and clinically interpretable machine learning methods in the field of quantitative analysis of neurodegenerative and neurodevelopmental diseases using various motor as well as non-motor digital biomarkers. In collaboration with neurologists from St. Anne's University Hospital in Brno and Central European Institute of Technology at Masaryk University, the developed methods will be integrated into systems based on Health 4.0 technologies.

   Tutor: Galáž Zoltán, Ing., Ph.D.

2. Electronically configurable analogue circuits

   This topic is focused on design of two-ports, filtering circuits especially and oscillators for instance, with possibility to externally and electronically change significant parameters of the circuit and in the case of filter also change of type of frequency response. Design with fractional-order element sis also expected. Available active elements are supposed to be used as it is or in modified variants. Simulations not only with simple models but also with transistor-level structures are expected. When verified by experimental measurement, behavioural modelling is preferred.

   Tutor: Jeřábek Jan, doc. Ing., Ph.D.

3. One class learning for visual anomaly detection of complex shapes

   One-class classification includes model learning techniques using "normal" data (or highly unbalanced data) and predicting whether new data is normal or anomaly when compared to the training data. This technique has a high potential for application in many scientific areas, especially in the field of visual quality control and products and e-health. The aim of the dissertation is the design and implementation of innovative techniques based on machine learning, which will be used for automatic detection of failures of complex shapes.

   Tutor: Burget Radim, doc. Ing., Ph.D.

4. Security in Converged Networks

   The aim is to analyse the up-to-date development and trends in the area of converged networks, mainly the problems of protection against cyber attacks. Design of innovative or new protection methods is supposed to be based on obtained observation. The research requires an orientation in the networks area, experience with MATLAB or SCILAB programs, and knowledge of at least one of VHDL, C or Java languages, evolutionary algorithms, and possibly use of the system FPGA.

   Tutor: Škorpil Vladislav, doc. Ing., CSc.

5. Spatiotemporal Analysis and Synthesis of Sound Field

   The spatiotemporal analysis displays the cumulative development of the sound field as a function of direction of the sound intensity using the spatial impulse response. Application of this method is, for example, an analysis of listening rooms, estimation of direction of the incoming sound and more. On the contrary, the spatiotemporal synthesis allows the perceptually based reproduction of 3D sound field for film and multimedia production, virtual and augmented reality or 360-degree video. The aim of dissertation thesis is research and development of methods of sound field pick-up using microphone arrays and subsequent synthesis for specific rendering systems.

   Tutor: Schimmel Jiří, doc. Ing., Ph.D.

6. Spatiotemporal Analysis and Synthesis of Sound Field

   The spatiotemporal analysis displays the cumulative development of the sound field as a function of direction of the sound intensity using the spatial impulse response. Application of this method is, for example, an analysis of listening rooms, estimation of direction of the incoming sound and more. On the contrary, the spatiotemporal synthesis allows the perceptually based reproduction of 3D sound field for film and multimedia production, virtual and augmented reality or 360-degree video. The aim of dissertation thesis is research and development of methods of sound field pick-up using microphone arrays and subsequent synthesis for specific rendering systems.

   Tutor: Schimmel Jiří, doc. Ing., Ph.D.