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Experiences from a new course in mechatronics at Technical University of Denmark are conveyed in this paper. The course is supposed to teach students enrolled in the bachelor degree in electrical engineering some fundamental knowledge about mechanics and to teach students enrolled in the bachelor degree in mechanical engineering fundamentals about electronics. Furthermore the course uses project work as a method to keep the students actively participating and in part have them teach each other the subjects. The general course plan is presented and the reasoning behind the course structure is discussed in the paper, together with a brief look at the student's reactions in form of data from the course evaluation.

In this paper, a method for identifying uncertain parameters in a rotordynamic system composed of a flexible rotating shaft, rigid discs and two radial active magnetic bearings is presented. Shaft and disc dynamics are mathematically described using a Finite Element (FE) model while magnetic bearing forces are represented by linear springs with negative stiffness. Bearing negative stiffness produces an unstable rotordynamic system, demanding implementation of feedback control to stabilize the rotordynamic system. Thus, to identify the system parameters, closed-loop system identification techniques are required., The main focus of the paper relies on how to effectively identify uncertain parameters, such as stiffness and damping force coefficients of bearings and seals in rotordynamic systems. Dynamic condensation method, i.e. pseudo-modal reduction, is used to obtain a reduced order model for model-based control design and fast identification., The paper elucidates how nodal parametric uncertainties, which are easily represented in the full FE coordinate system, can be represented in the new coordinate system of the reduced model. The uncertainty is described as a single column vector of the system matrix A of the full FE model while it is represented as several elements spread over multiple rows and columns of the system matrix of the reduced model. The parametric uncertainty, for both the full and reduced FE model, is represented using Linear Fractional Transformation (LFT). In this way the LFT matrices represent the mapping of the uncertainties in and out of the full and reduced FE system matrices. Scaling the LFT matrices easily leads to the amplitudes of the uncertainty parameters., Youla Parametrization method is applied to transform the identification problem into an open-loop stable problem, which can be solved using standard optimization methods., An example shows how to decouple and identify an uncertainty in the linear bearing stiffness of a reduced FE rotordynamic system.

In this paper we give an account of recent developments in the duality theory of Gabor frames. We prove the Wexler-Raz biorthogonality relations and the duality principle for co-compact Gabor systems on second countable, locally compact abelian groups G. Our presentation does not rely on the existence of uniform lattices in G.

This paper describes modeling, fabrication and high power optical characterization of thin gold films embedded in silicon dioxide. The propagation vector of surface plasmon polaritons has been calculated by the effective index method for the wavelength range of 750-1700 nm and film thickness of 15, 30 and 45 nm. The fabrication process of such plasmonic waveguides with width in the range of 1-100 μm and their quality inspection are described. The results of optical characterization of plasmonic waveguides using a high power laser with the peak power wavelength 1064 nm show significant deviation from the linear propagation regime of surface plasmon polaritons at the average input power of 100 mW and above. Possible reasons for this deviation are heating of the waveguides and subsequent changes in the coupling and propagation losses.

A new type of Marchand balun is presented in this paper, which has the property of complex impedance transformation. To allow the Marchand balun to transform between arbitrary complex impedances, three reactances should be added to the circuit. A detailed analysis of the circuit gives the governing equations. To verify the theory, a design and electromagnetic simulation of a lumped element Marchand balun is made in a SiGe BiCMOS technology. The lumped element impementation is favorable because capacitors are placed where the additional reactances should be added. Thus it is possible to absorb a positive reactance by reducing a capacitor. At the design frequency of 10.5 GHz it matches 50Ω to 50 - j66Ω. It has an insertion loss of 5.1 dB, an input reflection of −20.8 dB, as well as phase and magnitude imbalance better than 0.2° and 0.12 dB, respectively.

Non-negative Tensor Factorization (NTF) has become a prominent tool for analyzing high dimensional multi-way structured data. In this paper we set out to analyze gene expression across brain regions in multiple subjects based on data from the Allen Human Brain Atlas [1] with more than 40 % data missing in our problem. Our analysis is based on the non-negativity constrained Canonical Polyadic (CP) decomposition where we handle the missing data using marginalization considering three prominent alternating least squares procedures; multiplicative updates, column-wise, and row-wise updating of the component matrices. We examine three gene expression prediction scenarios based on data missing at random, whole genes missing and whole areas missing within a subject. We find that the column-wise updating approach also known as HALS performs the most efficient when fitting the model. We further observe that the non-negativity constrained CP model is able to predict gene expressions better than predicting by the subject average when data is missing at random. When whole genes and whole areas are missing it is in general better to predict by subject averages. However, we find that when whole genes are missing from all subjects the model based predictions are useful. When analyzing the structure of the components derived for one of the best predicting model orders the components identified in general constitute localized regions of the brain. Non-negative tensor factorization based on marginalization thus forms a promising framework for imputing missing values and characterizing gene expression in the human brain. However, care also has to be taken in particular when predicting the genetic expression levels at a whole region of the brain missing as our analysis indicates that this requires a substantial amount of subjects with data for this region in order for the model predictions to be reliable.

In this paper we consider single-carrier with frequency-domain equalization (SC-FDE) schemes where the transmission bandwidth is above the symbol rate. To allow high spectral efficiencies, several channels share the same bandwidth. Since the co-channel interference (CCI) levels can be very high, we propose iterative FDE receivers where we jointly detect all users sharing the same channel. Our performance results show that we can have excellent performances, even with several users sharing the same channel. In fact, we can have the maximum theoretical spectral efficiency even with signals that have bandwidth substantially above the symbol rate.