IT-Master Thesis Themes 2008

1. IT-Master Thesis Themes 2008 Discrete Systems Lab Prof. Dr.-Ing. Volker Lohweg Contact: volker.lohweg@fh-luh.de

2. Blind Signal Separation Methods for Machine Conditioning • Blind signal separation (BSS) is a method for separating mixed signals. Multiple sound or signal sources in a production machine are recorded by multiple sensors simultaneously. None of the signals contains the signal of a single source alone. By BSS the signals can be de-mixed again to a large extent. Actually most BSS algorithms are limited to the case of two sources and two sensors. • The goal of this thesis is to bring BSS to the real world. This involves mostly two steps: • Extending the number of sources, which can be handled simultaneously. How many channels can be handled in one BSS system? • Ensuring robustness in real world scenarios with a large number of (different) sensors interfering noise. Contact: Prof. Dr. Volker Lohweg, volker.lohweg@fh-luh.de Only valid with verbal explanation

3. The use of Kalman filters in sensor fusion • The Kalman filter is an efficient recursive filter which estimates the state of a dynamic system from a series of incomplete and noisy measurements. A wide variety of Kalman filters have now been developed, from Kalman's original formulation, now called the simple Kalman filter, to Schmidt's extended filter, the information filter and a variety of square-root filters developed by Bierman, Thornton and many others. • The goal of this thesis is to bring Kalman filter to the sensor fusion world. • Develop a signal analysis strategy for noisy multi sensor fusion concepts in the area of machine condition monitoring. • Show the feasibility of the strategy with Matlab/Simulink simulation. Contact: Prof. Dr. Volker Lohweg, volker.lohweg@fh-luh.de Only valid with verbal explanation

4. Design and Implementation of New Algorithmic Structures for Two-Dimensional Fast Integer Circular Transforms. • Circular transforms are of interest in the signal processing society because of their simple behavior regarding pattern recognition (separability properties) tasks. The thesis will focus on new algorithms for 2D circular transforms. It is widely known that different "classical" algorithms are available for 2D-transforms, such as Fourier- Walsh- and Cosine-Transform. It has to be proved, whether these algorithms can also used (in adopted form) or not. If not completely new concepts are necessary and should be worked out in the thesis. Contact: Prof. Dr. Volker Lohweg, volker.lohweg@fh-luh.de Only valid with verbal explanation

5. Research work: Design and prospective Implementation of a new coding sheme based on real or integer circular transforms and their phase spectra. • It is a known fact that the absolute value spectrum of the generalized circular transform operates on ld(N)+1 output coefficients (N: length of a data vector). The phase spectrum can be used to reconstruct the time signal, even if ld(N)+1 out coefficients are used. If it is possible to operate also on a reduced set of phase coefficients (data prediction) data reduction should be possible. Contact: Prof. Dr. Volker Lohweg, volker.lohweg@fh-luh.de Only valid with verbal explanation