Modeling of a constant Voltage transformer

This paper presents a comprehensive nonlinear model of the controlled constant voltage transformer also known as the ferroresonant transformer. Saturation is a normal mode of operation for this device. This paper derives an equivalent electrical circuit that relates to the physical structure of a typical design. The level of detail includes winding resistances, continuously nonlinear magnetizing inductances, tapped windings, and leakage inductances. The paper describes methods to extract the winding resistances, leakage inductances, and hysteresis loops of the transformer and how to fit the latter into single-valued nonlinear functions. The paper compares computer simulation results of the model with those obtained analytically and experimentally. The results show that the derived circuit will be very useful for designers of the ferroresonant transformer, which is used in uninterruptible power supplies.     

Some Insights into MIMO Mutual Information: The High SNR Case

We consider mutual information of multiple-input multiple-output (MIMO) wireless channels with complex isotropic Gaussian input in the case where the receiver has perfect channel, knowledge. For arbitrary fading statistics, a mutual information lower bound is decomposed in a sum of three terms involving: a) average SNR; b) channel fading; and c) a term characterizing the "effective rank", or eigenvalue dispersion, of the channel matrix. The decomposition suggests that spatial multiplexing efficiency of a MIMO channel can be characterized by the so-called ellipticity statistic. Distribution functions, means and variances of the random terms in the decomposition for the case of Rayleigh fading are also derived     

Combined RLS-LMS initialization for per tone equalizers in DMT-receivers

In discrete multitone receivers, the classical equalizer structure consists of a (real) time domain equalizer (TEQ) combined with complex one-tap frequency domain equalizers. An alternative receiver is based on a per tone equalization (PTEQ), which optimizes the signal-to-noise ratio (SNR) on each tone separately and, hence, the total bitrate. In this paper, a new initialization scheme for the PTEQ is introduced, based on a combination of least mean squares (LMS) and recursive least squares (RLS) adaptive filtering. It is shown that the proposed method has only slightly slower convergence than full square-root RLS (SR-RLS) while complexity as well as memory cost are reduced considerably. Hence, in terms of complexity and convergence speed, the proposed algorithm is in between LMS and RLS.     

Segmented polymer networks containing amino‐dendrimers

Polymer networks in which poly(propylene imine) dendrimers (Astramol?) are connected to each other by linear polytetrahydrofuran (polyTHF) segments, were prepared by two methods. The first method was a one‐step procedure in which bifunctionally living polyTHF, obtained by initiation of the THF polymerization with trifluoromethane sulfonic anhydride (triflic anhydride), was reacted with an amino‐dendrimer. This reaction was very fast but did not allow formation of the end products. The second method was a two‐step procedure. In a first step, living polyTHF, prepared with acryloyloxybutyl triflate as initiator, was grafted on an amino‐dendrimer, to form a star‐like, acrylate‐terminated polyTHF multi‐macromonomer with the dendrimer as core. In a second step, networks were obtained by Michael addition between the acrylate end‐groups and unreacted amino‐groups of the dendrimer. This cross‐linking reaction occurred spontaneously upon heating of the solution of the multi‐macromonomer with gelation times varying from a few minutes to a few hours, depending on the temperature and the composition of the prepolymers. With this method it was possible to prepare networks in the form of coatings or films. © 2003 Society of Chemical Industry     

Low Temperature Physics at the Laboratoire National des Champs Magnétiques Pulsés in Toulouse

An overview over past and present activities and future developments at the Toulouse pulsed magnetic field facility is given, both as far as technical developments of the infrastructure, as well as low temperature physics performed at the LNCMP are concerned.     

Volumetric Change and Surface Properties of Temperature-Sensitive Polyvinylalcohol (PVA) Hydrogel

Polyvinylalcohol (PVA) polymer gel is a temperature sensitive polymeric gel, with a critical transition temperature (with H₂O) of 310 K. At higher than 310 K, this temperature sensitive polymer gel shrinks because of discharging water, whereas at lower temperatures, the gel swelled because of absorbing water. The reversibility of the gel's volume change was confirmed by temperature swing. The adsorption behavior of an organic compound onto the PVA polymer gel in water was tested at various temperatures. The amount of adsorbed organic compound increased remarkably at temperatures higher than about 310 K. Then, it was confirmed that the organic compound in PVA polymer gel could be reversibly adsorbed and desorbed by a temperature change between 293 and 323 K. The mechanism of adsorption of the organic compound onto the PVA polymer gel could be explained by hydration and dehydration of polymer gel.     

Quantifying and characterizing contemporary riparian sedimentation

Fluvial processes of erosion, sediment transport and deposition determine the changing form and sedimentary structure of naturally adjusting riparian zones. Riparian sediment storage has both scientific and management importance in relation to: (i) the quantities of sediment that are involved; (ii) the quality of the sediment; and (iii) the dispersal of biological materials, notably the vegetation propagules that are transported and deposited in association with the sediment. After discussing the significance of riparian sedimentation processes, this paper reviews methods for quantifying contemporary sediment deposition within water bodies and their margins. Methods for investigating contemporary riparian sedimentation are given particular emphasis, and the extent to which different methods provide comparable estimates and have been used to support the analysis of different physical and chemical properties of the sediment are outlined. The importance of the following are stressed: (i) selecting a sampling method that is suited to the sedimentation environment; (ii) incorporating careful cross‐calibration if measurements from different methods are to be combined; and (iii) replicating measurements to give more robust estimates if small traps are employed. It is concluded that artificial turf mats provide a useful design of sediment trap across a range of environmental conditions because: (i) their surface roughness reduces problems of sediment removal by flood waters or rainfall; (ii) their pliability permits installation on irregular surfaces; (iii) they can be securely attached to the ground with metal pins to resist high shear stresses from river flows; (iv) they are robust and light and so easily manipulated in the field and laboratory; (v) it is possible to fully recover the deposited sediment to accurately determine the amount of sediment deposited and to support a range of other analyses. Results are presented to illustrate how artificial turf mats can be used to estimate the quantity and quality of deposited sediment and to explore the associated deposition of viable seeds. This provides one example of the important hydroecological role of riparian sedimentation processes and of the potential for the development of innovative, interdisciplinary research on riparian sediment dynamics. Copyright © 2003 John Wiley & Sons, Ltd.     

Microstrip stepped impedance resonator bandpass filter with an extended optimal rejection bandwidth

Bandpass filters with an optimal rejection bandwidth are designed using parallel-coupled stepped impedance resonators (SIRs). The fundamental (f/sub o/) and higher order resonant harmonics of an SIR are analyzed against the length ratio of the high-Z and low-Z segments. It is found that an optimal length ratio can be obtained for each high-Z to low-Z impedance ratio to maximize the upper rejection bandwidth. A tapped-line input/output structure is exploited to create two extra transmission zeros in the stopband. The singly loaded Q(Q/sub si/) of a tapped SIR is derived. With the aid of Q/sub si/, the two zeros can be independently tuned over a wide frequency range. When the positions of the two zeros are purposely located at the two leading higher order harmonics, the upper rejection band can be greatly extended. Chebyshev bandpass filters with spurious resonances up to 4.4f/sub o/, 6.5f/sub o/, and 8.2f/sub o/ are fabricated and measured to demonstrate the idea.     

Classification of audio radar signals using radial basis function neural networks

Radial basis function (RBF) neural networks are used to classify real-life audio radar signals that are collected by a ground surveillance radar mounted on a tank. Currently, a human operator is required to operate the radar system to discern among signals bouncing off tanks, vehicles, planes, and so on. The objective of this project is to investigate the possibility of using a neural network to perform this target recognition task, with the aim of reducing the number of personnel required in a tank. Different signal classification methods in the neural net literature are considered. The first method employs a linear autoregressive (AR) model to extract linear features of the audio data, and then perform classification on these features, i.e, the AR coefficients. AR coefficient estimations based on least squares and higher order statistics are considered in this study. The second approach uses nonlinear predictors to model the audio data and then classifies the signals according to the prediction errors. The real-life audio radar data set used here was collected by an AN/PPS-15 ground surveillance radar and consists of 13 different target classes, which include men marching, a man walking, airplanes, a man crawling, and boats, etc. It is found that each classification method has some classes which are difficult to classify. Overall, the AR feature extraction approach is most effective and has a correct classification rate of 88% for the training data and 67% for data not used for training.