Gerwald Lichtenberg

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This paper shows the successful application of an iterative learning controller (ILC) to the Free Electron Laser FLASH at DESY, Hamburg, a plant of large international interest for research in physics, chemistry, biology, and engineering. First experimental results demonstrate the applicability of the ILC approach to the low level radio frequency system(More)
A new approach for modelling the dynamics of gene expression from time series microarray data is presented. A modelling method based on a continuous representation of Boolean functions in the form of Zhegalkin Polynomials is proposed. Structural information known from theoretical biology like the canalizing property can be included as well as continuous(More)
Iterative Learning Control (ILC) has been especially developed to improve the performance of systems that operate in a repetitive manner where the task is to follow some specified trajectory in a specified finite time interval, also known as a pass or a trial in the literature, with high precision. The novel principle behind ILC is to suitably use(More)
Iterative Learning Control (ILC) has been especially developed to improve the performance of systems that operate in a repetitive manner where the task is to follow some specified trajectory in a specified finite time interval, also known as a pass or a trial in the literature, with high precision. The novel principle behind ILC is to suitably use(More)
The operation of a Free Electron Laser in the X-ray wavelength range is the goal of the international XFEL project. The project critically depends on the linear accelerator component, where radio frequency fields have to be controlled with a very high amplitude and phase precision and under various sources of disturbances. This paper is about finding(More)
It has been observed that genetic regulatory networks share many characteristics with Boolean networks such as periodicity, self organization etc. Moreover it is also a known fact that in these networks, most genes are governed by canalizing Boolean functions. However, the actual gene expression level measurements are continuous valued. To combine discrete(More)
Der Beitrag beschreibt einen neuen Ansatz zur Modellierung des dynamischen Verhaltens der Genexpression. Im Gegensatz zu bekannten Modellbildungsmethoden können mit Hilfe der vorgestellten Methode sowohl diskrete biologische Regeln, wie z.B. die kanalisierenden Eigenschaft der Gen-Wechselwirkung, als auch kontinuierliche Messdaten berücksichtigt werden.(More)
In gene dynamics modeling, parameters of Boolean networks are identified from continuous data under various assumptions expressed by logical constraints. These constraints may restrict the dynamics of the network to the subclass of canalyzing functions, which are known to be appropriate for genetic networks. This paper introduces a high performance(More)