A new family of soft transition converters: Design and dynamic model

The soft switching converters evolved through the resonant load, resonant switch, resonant transition and active clamp converters to eliminate switching losses in power converters. This paper briefly presents the operating principle of the new family of soft transition converters; the methodology of design of these converters is presented through an example. In the proposed family of converters, the switching transitions of both the main switch and auxiliary switch are lossless. When these converters are analysed in terms of the pole current and throw voltage, the defining equations of all converters belonging to this family become identical.Such a description allows one to define simple circuit oriented model for these converters. These circuit models help in evaluating the steady state and dynamic model of these converters. The standard dynamic performance functions of the converters are readily obtainable from this model. This paper presents these dynamic models and verifies the same through measurements on a prototype converter.

Design and Optimization of Broadband Micromachined Antenna

Performance improvement of a micromachined patch antenna operating at 30 GHz with a capacitively coupled feed arrangement is presented here. Such antennas are useful for monolithic integration with active components. Specifically, micromachining can be employed to achieve a low dielectric constant region under the patch which causes (i) the suppression of surface waves and hence the increase in radiation efficiency and (ii) increase in the bandwidth. The performance of such a patch antenna can be significantly improved by selecting a coupled feed arrangement. We have optimized the dimensions and location of the capacitive feeding strip to get the maximum improvement in bandwidth. Since this is a totally planar arrangement, and does not involve any stacked structures, this antenna is easy to fabricate using standard microfabrication techniques. The antenna element thus designed has a -10 dB bandwidth of 1600 MHz

Decision tree design and applications in speech processing

The design and operation of the minimum cost classifier, where the total cost is the sum of the measurement cost and the classification cost, is computationally complex. Noting the difficulties associated with this approach, decision tree design directly from a set of labelled samples is proposed in this paper. The feature space is first partitioned to transform the problem to one of discrete features. The resulting problem is solved by a dynamic programming algorithm over an explicitly ordered state space of all outcomes of all feature subsets. The solution procedure is very general and is applicable to any minimum cost pattern classification problem in which each feature has a finite number of outcomes. These techniques are applied to (i) voiced, unvoiced, and silence classification of speech, and (ii) spoken vowel recognition. The resulting decision trees are operationally very efficient and yield attractive classification accuracies.

Composite instantaneous comparators basis for design and their transient performance

Principles of design of composite instantaneous comparators (a combination of amplitude- and phase- comparison techniques) are laid out to provide directional, directional-reactance, nonoffset-resistance and conductance characteristices. The respective signals provided by the voltage transformer and the current transformer are directly used as relaying signals without resorting to any form of mixing. Phase shifts required, are obtained by using magnetic ferrite cores in a novel manner. Sampling units employing a combination of ferrite cores and semiconductor devices provide highly reliable designs. Special attention is paid to the choice of relaying signals, to eliminate the need for any synchronisation or modification and to avoid `image¿ characteristics. These factors have resulted in a considerable simplification of the practical circuitry. A thyristor AND circuit is employed in dual comparator units to provide the final tripping, and leads to a circuit which is much less sensitive to extraneous signals than a single-thyristor unit.

Design and performance analysis of a signal detector based on suprathreshold stochastic resonance

This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation sigma of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum sigma also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum sigma depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. (C) 2012 Elsevier B.V. All rights reserved.