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. Artificial intelligence for fingerprint degradation

   One of the latest advances in fingerprinting and artificial intelligence research involves the use of deep learning algorithms to automate the fingerprint identification process. These algorithms can analyze large databases of fingerprints and quickly compare an unknown fingerprint to a known one with high accuracy. The main advantage over previous methods is the ability of deep learning algorithms to learn to recognize and interpret complex patterns and relationships in image data. In this way, deep learning algorithms can overcome the limitations of previous methods, which often depended on hand-crafted rules and limited parameters for fingerprint recognition. The aim of the dissertation is to develop techniques based on machine learning for the objective assessment of ancillary information associated with a dactyloscopic print, such as its age with respect to environment and weather conditions.

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

2. Converged networks with limited bandwidth

   Converged networks with limited bandwidth require a research of alternatives of increasing their throughput. It is about solving the problems connected with broadband data transmission, which is in certain parts limited by a narrower bandwidth, the so-called bottleneck problem. Come up with solution possibilities and subsequently design, model and implement a new system on the NetCOPE platform. Consider solutions based on QoS, solutions based on compression algorithms, and their combinations. Knowledge in the area of IP networks, modelling in MATLAB and Simulink, and programming in languages VHDL or Verilog are supposed. You are supposed to compare your system with existing ones and to specify its advantages.

   Tutor: Škorpil Vladislav, doc. 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. Parallelization of Evolutionary Algorithms

   The aim is research in the field of evolutionary algorithms parallelization. Parallelization is an integral part of an endeavour to increase effectiveness of evolutionary 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. Research should be concentrated on the island models of evolutionary algorithms. 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.

6. Scalable quantum networks

   The aim is research and development in the field of quantum networks and their simulators, specifically network architectures and protocols and the possibilities of their simulation and testing. Start from your own design of the simulation environment for testing purposes and define the advantages and disadvantages of individual solutions. Use Python or another suitable programming language. An introductory simulator is available at https://netsquid.org/. Direct the work towards optimization especially from the point of view of security and post-quantum data processing with reach to the network layer according to TCP/IP.

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

7. 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. The areas of 5G mobile, SDN (Software Defined Networks) and related transmission technologies are seemed to be among the perspective possibilities. 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.

8. 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.

9. 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 01.04.2023 to 30.04.2023)

1. Optical fiber infrastructure security

   Fiber optic networks have evolved rapidly in recent years to meet the ever-increasing demand for increasing capacity. Today, optical fibers are widely used in all types of networks due to not only transmission speed or maximum achievable distance but also security. Although fiber optic networks are considered completely secure, there are ways to capture or copy part of the data signal. Both imperfections of passive optical components and, for example, monitoring outputs of active devices can be used. With the advent of quantum computers, current encryption could be broken. It is therefore necessary to address the security of fiber-optic networks, analyze security risks and propose appropriate countermeasures.

   Tutor: Münster Petr, doc. Ing., Ph.D.