Currently the DSS group offers only one seminar. You can find some details below.
Selected Topics in Digital Signal Processing
|Lecturers:||Gerhard Schmidt and group|
|Language:||English or German|
|Target group:||Master students in electrical engineering and computer engineering|
|Prerequisites:||Fundamentals in digital signal processing|
If you want to sign up for this seminar, you need to register with the following information in the registration form
Please note that the registration period starts 01.10.2018 at 8:00 h and ends 21.10.2018 at 23:59 h. All applications before and after this registration period will not be taken into account.
Registration will be possible within the before mentioned time under the following subsite - Seminar Registration.
During the registration process you will also choose your seminar topic. Only one student per topic is permitted (first come - first serve).
Students write a scientific report on a topic closely related to the current research of the DSS group. Potential topics, therefore, deal with digital signal processing regarding:
Students will also present their findings in front of the other participants and the DSS group.
Topics offered in WS 18/19
Speech and Audio:
Unsupervised Learning for Neural Networks
It is often hard to obtain enough labeled data to train an artificial neural network (ANN) using supervised learning algorithms. Here, unsupervised learning can be a solution, by exploring data where the result or classification is not known, to find new features or classifications. Aim of this seminar is to present the typical unsupervised learning methods and self-taught ANNs, like for example self-organizing feature maps.
Speech Quality Estimation by means of Speech Recognition
Speech quality is most often estimated by extracting signal features and mapping their values towards an overall quality score. Nowadays, this mapping may also be performed by classifiers or, generally, by methods developed in a pattern recognition context. Another modern approach is to abandon the classical speech quality features altogether and to make use of speech recognition models instead, where both the recognition rate and internal values may be used to approximate the speech quality score. For this topic, the different quality estimation schemes which make use of a speech recognizer should be outlined and compared.
Neural Network Topologies
Whenever a large set of training data is available, artificial neural networks are an alternative compared to classical classification and estimation methods. Depending on the application, however, a specific network topology is advantageous and should, therefore, be selected. For this topic, commonly used network topologies should be analysed and compared in order to give a recommendation for their prefered area of application.
Acoustic Artifacts Imposed by Speech Enhancement Systems
Communication systems such as ICC systems or communication units in firefighter breathing mask are implemented to enhance communication between two or more persons or parties. Often, such systems have to deal with several challenges at one time. Therefore, some unwanted effects may occur. The aim of this seminar is to review the mentioned systems regarding possible unwanted effects.
Simulation of Motor Unit and Nerve Potentials and Typical Model Parameters
Electroneuography (ENG) is the current gold standard of nerve assessment to investigate different signals of the nerve in the clinical environment. The electrical signal of peripheral nerves is quite low. Peak amplitudes in the mV range can be observed by using an external electric stimulation of the nerve. The electrical signal produced by the muscles also lies in the mV range. Different simulations are already published with different model parameters to access the individual signals of nerve fibers. This helps to simulate different human nerve diseases. Available simulations and also typical simulation parameters should be investigated from a signal analysis point of view in this seminar.
Functionality of Volterra Filters and their Usage for an Improved Sensor Performance
Many sensors suffer from nonlinear effects and are, thus, limited in performance. These nonlinear effects can be caused by the sensor itself, the used hardware, or its surroundings. In this seminar, Volterra filters should be considered for performance improvement of sensors by means of literature study. The improvement should should manifest in terms of a better system identification and noise cancellation. A comparison to other nonlinear filters is preferable.
Achieving Orthogonality under Constraints Preset by given Hardware Limitations of SONAR Systems
The essential advantage of MIMO SONAR systems yields from the possibility to transmit nearly perfectly orthogonal sequences. Given the assumption that all transmitted orthogonal sequences can be recovered at the receive side, this leads to a more sophisticated processing and more flexibility e.g. due to “offline” changeability of “transmit” beamforming directions.
In this seminar, first orthogonality should be specified and based on this, possible (not necessarily perfect) techniques to achieve orthogonality of signals should be examined and discussed. All investigations should be done under the consideration of given hardware/software limitations. Conclusively, the impact of non-perfect orthogonality should be considered given previous findings.
Tracking of Multiple Targets using Joint Probabilistic Data Association
Target tracking in both SONAR and Radar applications make use of the Probabilistic Data Association (PDA) method. The method is suitable for tracking of one or more targets, in case they are well separated. However, if there are several target objects, events can occur in which a measurement is associated with several tracks. This is exactly the case when the measurement is in the gating range of two or more targets. In order to master these events, the Joint Probabalistic Data Assiciation (JPDA) method is often used. As part of this seminar topic, the last five scientific papers on this topic are to be found and summarized into one paper. For the beginning, some papers of renowned authors will be provided.
Speech Coding for Underwater Communication
The underwater acoustic channel is one of the most challenging channels for communication. Because of damping and dispersion, high-frequency communication is not usable for longer distances underwater. Low data-rates and rapidly changing channel characteristics make stable digital communication links hard to achieve. Speech can be transmitted by analog modulation schemes, but this technique occupies a high bandwidth. Therefore, digital speech transmission in the underwater domain needs robust speech coding, which is on the one hand capable of dealing with transmission errors, and on the other hand only uses a low data-rate and bandwidth. In this seminar, different speech coding techniques should be examined for their applicability in underwater communication and, finally, a recommendation should be given for short- to mid-range underwater telephony.