This area of concentration is divided into Communications and Digital Signal Processing.
Recent advances in telecommunication systems have allowed an intense exchange of information between people and organizations. This has improved several aspects of daily life in terms of entertainment, education, health or business. New standards for data transmission are being offered at an accelerated pace to enable communication via radio frequency for different purposes (digital television, mobile telephony, internet, software radio, telemedicine, WiMax, among others). The implementation and perfecting of these standards (with the employment of recent technology) involves knowledge of electronics, computer programming, digital signal processing and communication theory.
The combination of courses in the area of Communications and Signal Processing provides a solid and up-to-date training which prepares the graduate student to undertake cutting-edge research, as well as to meet the growing demand for professionals to research and develop in companies of the communications sector. The courses involve a wide range of communication systems technology, including digital signal processing, channel equalization and coding, mobile communication and MIMO-OFDM systems.
Researchers at PPGEEL, including students, have been contributing to the development of this area through partnerships with companies and universities. Among the partners are: Conservatoire National des Arts et Métiers (CNAM, France), University of Sydney (Australia), University of Toronto (Canada), and the Brazilian institutions UNICAMP, UFPE, UTFPR, UFSM, UFC, CEFET- CE and INATEL.
- Smart Antennas
- Channel Coding
- Cooperative Communication
- Network Coding
- Software-Defined Radio
- MIMO Communication Systems
- OFDM/FBMC Multicarrier Communication Systems
- Information Theory
- Digital TV
Digital Signal Processing
Research in signal processing aims to advance the study of algorithms and structures for different applications. Basic and applied research is undertaken to improve the performance of current algorithms and signal processing structures. A signal is a collection of information which can be stored, transmitted or used to make decisions. Typical signals found in daily life include voice, music, image and stock exchange indexes. A signal is a function of one or more variables such as time, distance, position, temperature or pressure. A signal carries information and the aim of signal processing is to extract the information from the signal.
The best technique to extract this information depends on the type of signal and the nature of the information it is carrying. Signal processing deals with the mathematical representation of the signal and with the mathematical and algorithmic operations carried out to extract the desired information. The mathematical representation can use continuous or discrete variables (for example, continuous-time or discrete-time signals).
The operations can be carried out by circuits or by mathematical algorithms inserted in computers or in programmable integrated circuits of specific application (digital signal processers) or of general use. Research in signal processing includes analysis, design, and optimization of algorithms and structures to process signals in a variety of applications.
Faculty and researchers in the area of signal processing are involved with applications such as image processing, speech signal processing, acoustic signal processing, biomedical signal processing and general data processing.
Subjects such as image and voice coding, visual inspection, acoustic noise and vibration control, analogue and digital filtering for different purposes, adaptive filtering, detection, estimation and classification of signals, recognition of standards, estimation and equalization of communication channels, and processing using arrays are examples of research fields in which master’s theses and doctoral dissertations have been conducted.
These areas offer stimulating challenges to students interested in tackling modern engineering issues. Several of the research projects in the field of signal processing are carried out in cooperation with other research institutions in different Brazilian States and abroad (in countries such as the United States and France), as well as in partnership with national and multinational companies. Doctoral students can do internships abroad for 6 to 12 months.
In image processing, the research is oriented to image coding, video coding, recognition of standards and its applications, automatic algorithms for visual inspection and watermarking algorithms in images, videos, voice and printed documents for security, authentication, copyright and forensic analysis.
Regarding voice processing, the research efforts are concentrated in the areas of coding, recognition, IP packet network transmission and voice signal synthesis.
Research in adaptive filtering focuses on the analysis and design of linear and non-linear algorithms for adaptive filtering and on acoustic and line echo cancelling in communication systems.
In biomedical signal processing, the studies approach hearing devices, EEG and ECG signal processing, and techniques for evoked potential estimation.
Some of the institutions currently involved in research and development projects are: University of California, Irvine, USA; Laboratoire des Signaux et Systèmes, C.N.R.S., France; Universidade Estadual de Campinas (UNICAMP), Brazil; the national companies Dígitro Tecnologia Ltda., and Intelbrás; and the international company Hewlett-Packard Labs (USA).
- Adaptive Filtering
- Biomedical Instrumentation
- Digital Signal Processing
- Biomedical Digital Signal Processing
- Image and Video Digital Processing
- Statistical Signal Processing of Signal (estimation, detection, classification, standard recognition)
- Speech Recognition
- Techniques for marking and securing voice, image and video signals and printed documents
- Systems for communication of voice signals over IP packet networks of IP packet (VOIP)
- Laboratory of Communications, Signal Processing and Machine Learning – LCS
- Circuits and Signal Processing Laboratory – LINSE
- Digital Signal Processing Research Laboratory - LPDS
- Bartolomeu F. Uchôa Filho (Channel Coding, Cooperative Communication, Network Coding)
- Bruno Catarino Bispo (Speech and Biomedical Signal Processing, Adaptive Filtering, Machine Learning)
- Danilo Silva (Machine Learning and Applications)
- Eduardo Luiz Ortiz Batista (Adaptive Filtering, Beamforming, Hardware Implementation of Digital Signal Processing Systems, Machine Learning)
- José Carlos Moreira Bermudez (Adaptive Filtering, Estimation, Detection, Classification, Recognition of Standards)
- Márcio Holsbach Costa(Adaptive Filtering)
- Raimes Moraes
- Richard Demo Souza
- Rui Seara
EEL 410250 – Machine Learning (4 credits)
EEL 510237 – Stochastic Processes (4 credits)
EEL 510241 – Digital Communication (4 credits)
EEL 510273 – Speech Processing (2 credits)
EEL 510274 – Advanced Digital Signal Processing: Techniques and Applications (4 credits)
EEL 510275 – Wireless Communications (4 credits)
EEL 510276 – Error-Correcting Codes (4 credits)
EEL 510384 – Digital Signal Processing (4 credits)