The following selection of our current research projects shall give you an insight look into the variety of our topics. More projects can be found on the respective websites of the fields of work.

Sparse Coding Approaches to Language Acquisition

One of the scientific challenges is the understanding of the efficiency, flexibility and intelligence of biological systems. Their ability to is their ability to learn, viz. aquire knowledge of the interaction with the environment, in order to use it later among the characteristics. In this context the priority programme pursues the problem of autonomy. Instead we pursue the aim of autonomous learning, viz. independent learning, independent collection of information about a complex environment and independent education about structured re–presentation and generalized models of what has been learned.

This project at the University of Paderborn aims at the development of one of the systems for learning of reference pattern for unsupervised learning of a language. The machine shall descover recurring patterns within the continous spoken entering speech signal and learn an inventory of units, namely on two different levels of abstraction: on the one hand on the level of sounds and on the other hand on the level of words. Procedures are supposed to be used from the area of sparse coding in order to find a representation of a speech signal which is fed by the presentation of the speech signal within the short–term spectral range by dint of a linear combination of basic vectors. While non­­–negative matrix factorization (NMF) has already been used upon language, there are other procedures which require the non–negativity of matrix elements, so they can be applied better for the common parameterization of speech signals, as the Mel-Frequency Cepstral Coefficients. A promising procedure is the k-singular value decomposition (k-SVD), which so far has been primarily applied in computer vision. All of these learning procedures have to be extended, so they can add to the learning of typical spectral patterns and gather temporal correlation of speech signals. In addition approaches out of the area of dynamic time adjustment and speech recognition based on the "hidden" Markov–model are applied. On the first, lower level of the decomposition of the entering speech signal recurring sound units shall be discovered. On the second, higher level of abstraction word or phrases units similar to the procedure on the first level are learned, based upon a description of the lower levels with the help of n-grams, viz. with the help of the frequency of sound units. The lower level shall hand down the posteriori probabilities to the higher level, so an premature definite decision concerning the sounds can be avoided.

This project is one of 15 projects in the SPP "Autonomous Learning" of the DFG.

http://nt.uni-paderborn.de/studentische-arbeiten/

Integration of individual particles-field effect-transistors

Pushed by the enormous cost pressure within the semiconductor industry, possibilities for the implementation with low performance requirements (e.g. Transponder, Smart Cards, Control of medical sensors and actuators for one–time usage, etc.) are developed for producing a so–called "low–cost / low–performance"–engineering. A lot of scientists use organic transistors (OFET) for it, which show very little carrier mobilities and very fast degradation.

In the field of work of sensor technology research is done in the area of integration of field effect-transistors which use inorganic nanoparticles as semiconductor material. In comparison these particles perform well at low cost. In order to increase the mobility of the charge carrier inside the channel and to reduce the arising forfeiture caused by interparticle processes the research focus lies on producing single particle transistors upon different substrates. In this case the channel made of a single semiconducted nanoparticle. Introducing the nanoparticle into the channel is achieved with the help of surface–wide spin–coatings of a dispersion.

Different from conventional MOSFETs a transistor based on nanoparticles depend on the Schottky–effect, which appears at the transition from metal to semiconductor. Adjustment processes of the respective Fermi–levels lead to a development of barrier layers, the so–called Schottky–barriers. It means for the transistors that the Drain– as well as the Source–contacts barriers, which pervent an electricity flow, are trained so that the tranistor is blocked. The creation of a control voltage within the gate–electrode results in an inversion layer and the reduction of barrier width, so that a transmission probability of charge carriers increase and which conducts transistors.

Development of architectures of a KMU–Microgrids with intelligent power controller

The predicted change in the energy revolution caused by renewable energies puts industry nations including Germany in front of great challenges: a reliable, sustainable and cost–effective energy supply has to be guaranteed. An intelligent decentralisation of the power supply is necessary, so especially domestic energies like sun, water, wind and gas heatering can be used efficiently. In doing so deviating the creation of electrical energy in large power stations and down to small power stations (Microgrids) is necessary. These are placed near the consumer and are only linked to the central electricity grid when necessary. An important group of consumers are small and medium–sized companies (KMU), which at large need the most amount of the electrical power in Germany.

The project is promoted by BMBF within the technology network it’s OWL as an innovation project. The industrial partners in this project is the AEG Power Solutions.

https://www.its-owl.com/projects/innovation-projects/