923 resultados para Input-output


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Cascaded multilevel inverters synthesize a medium-voltage output based on a series connection of power cells which use standard low-voltage component configurations. This characteristic allows one to achieve high-quality output voltages and input currents and also outstanding availability due to their intrinsic component redundancy. Due to these features, the cascaded multilevel inverter has been recognized as an important alternative in the medium-voltage inverter market. This paper presents a survey of different topologies, control strategies and modulation techniques used by these inverters. Regenerative and advanced topologies are also discussed. Applications where the mentioned features play a key role are shown. Finally, future developments are addressed.

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A method is developed by which the input leading to the highest possible response in an interval of time can be determined for a class of non-linear systems. The input, if deterministic, is constrained to have a known finite energy (or norm) in the interval under consideration. In the case of random inputs, the energy is constrained to have a known probability distribution function. The approach has applications when a system has to be put to maximum advantage by getting the largest possible output or when a system has to be designed to the highest maximum response with only the input energy or the energy distribution known. The method is also useful in arriving at a bound on the highest peak distribution of the response, when the excitation is a known random process.As an illustration the Duffing oscillator has been analysed and some numerical results have also been presented.

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The paper presents simple graphical procedures for position synthesis of plane linkage mechanisms to generate functions of two independent variables. The procedures are based on point-position reduction and permit synthesis of the linkage to satisfy up to six arbitrarily selected precision positions.

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The transition time associated with the time-variation of the voltage across a two-terminal diaphragm-less solion in response to a step-current stimulus has been studied experimentally. A theoretical analysis has also been made by solving the diffusion problem under the appropriate initial and boundary conditions. The behaviour of the theoretically predicted transition times is in agreement with the observed behaviour. The systems under study have been shown to be different from those used hitherto in thin-layer chronopotentiometry.

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The transition time associated with the time-variation of the voltage across a two-terminal diaphragm-less solion in response to a step-current stimulus has been studied experimentally. A theoretical analysis has also been made by solving the diffusion problem under the appropriate initial and boundary conditions. The behaviour of the theoretically predicted transition times is in agreement with the observed behaviour. The systems under study have been shown to be different from those used hitherto in thin-layer chronopotentiometry.

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The performance of a plate clutch in a two-inertia power transmission system is analysed assuming negligible compliance and using a piecewise linear function to represent the clutch torque characteristic. Expressions defining, for all linear segments of the clutch torque characteristic, dimensionless input and output velocities of the clutch and dimensionless slip period are presented. The use of these expressions in preparing design charts to aid analysis and design of the plate clutch is outlined.

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In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

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The numbers and mean radio luminosities of giant radio galaxies (GRGs) have been calculated for redshifts up to z = 0.6, assuming a sensitivity limit of 1 Jy at 1 GHz for the observations. The estimates are obtained with a model for the beam propagation, first through the hot gaseaous halo around the parent galaxy, and thereafter, through the even hotter but less dense intergalactic medium. The model is able to accurately reproduce the observed numbers and mean radio luminosities of GRGs at redshifts of less than 0.1, and it predicts that a somewhat larger number of GRGs should be found at redshifts of greater than 0.1.