583 resultados para 290900 Electrical and Electronic Engineering


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This research published in the foremost international journal in information theory and shows interplay between complex random matrix and multiantenna information theory. Dr T. Ratnarajah is leader in this area of research and his work has been contributed in the development of graduate curricula (course reader) in Massachusetts Institute of Technology (MIT), USA, By Professor Alan Edelman. The course name is "The Mathematics and Applications of Random Matrices", see http://web.mit.edu/18.338/www/projects.html

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This paper presented results from a details and comprehensive simulation using finite element method of the practical operation of an electrical machine. The results it displayed have been used in practice to design more efficient equipment.

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Wavelets introduce new classes of basis functions for time-frequency signal analysis and have properties particularly suited to the transient components and discontinuities evident in power system disturbances. Wavelet analysis involves representing signals in terms of simpler, fixed building blocks at different scales and positions. This paper examines the analysis and subsequent compression properties of the discrete wavelet and wavelet packet transforms and evaluates both transforms using an actual power system disturbance from a digital fault recorder. The paper presents comparative compression results using the wavelet and discrete cosine transforms and examines the application of wavelet compression in power monitoring to mitigate against data communications overheads.

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Feature selection and feature weighting are useful techniques for improving the classification accuracy of K-nearest-neighbor (K-NN) rule. The term feature selection refers to algorithms that select the best subset of the input feature set. In feature weighting, each feature is multiplied by a weight value proportional to the ability of the feature to distinguish pattern classes. In this paper, a novel hybrid approach is proposed for simultaneous feature selection and feature weighting of K-NN rule based on Tabu Search (TS) heuristic. The proposed TS heuristic in combination with K-NN classifier is compared with several classifiers on various available data sets. The results have indicated a significant improvement in the performance in classification accuracy. The proposed TS heuristic is also compared with various feature selection algorithms. Experiments performed revealed that the proposed hybrid TS heuristic is superior to both simple TS and sequential search algorithms. We also present results for the classification of prostate cancer using multispectral images, an important problem in biomedicine.

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Germanium (Ge) does not grow a suitable oxide for MOS devices. The Ge/dielectric interface is of prime importance to the operation of photo-detectors and scaled MOSTs. Therefore there is a requirement for deposited or bonded dielectric materials. MOS capacitors have been formed on germanium substrates with three different dielectric materials. Firstly, a thermally grown and bonded silicon dioxide (SiO2) layer, secondly, SiO2 deposited by atmospheric pressure CVD ‘silox’, and thirdly a hafnium oxide (HfO2) high-k dielectric deposited by atomic layer deposition (ALD). Ge wafers used were p-type 1 0 0 2 O cm. C–V measurements have been made on all three types of capacitors to assess the interface quality. ALD HfO2 and silox both display acceptable C–V characteristics. Threshold voltage and maximum and minimum capacitance values closely match expected values found through calculation. However, the bonded SiO2 has non-ideal C–V characteristics, revealing the presence of a high density of interface states. A H2/N2 post metal anneal has a detrimental effect on C–V characteristics of HfO2 and silox dielectrics, causing a shift in the threshold voltage and rise in the minimum capacitance value. In the case of hafnium dioxide, capacitor properties can be improved by performing a plasma nitridation of the Ge surface prior to dielectric deposition.

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This letter reports the statistical characterization and modeling of the indoor radio channel for a mobile wireless personal area network operating at 868 MHz. Line of sight (LOS) and non-LOS conditions were considered for three environments: anechoic chamber, open office area and hallway. Overall, the Nakagami-m cdf best described fading for bodyworn operation in 60% of all measured channels in anechoic chamber and open office area environments. The Nakagami distribution was also found to provide a good description of Rician distributed channels which predominated in the hallway. Multipath played an important role in channel statistics with the mean recorded m value being reduced from 7.8 in the anechoic chamber to 1.3 in both the open office area and hallway.

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High-speed field-programmable gate array (FPGA) implementations of an adaptive least mean square (LMS) filter with application in an electronic support measures (ESM) digital receiver, are presented. They employ "fine-grained" pipelining, i.e., pipelining within the processor and result in an increased output latency when used in the LMS recursive system. Therefore, the major challenge is to maintain a low latency output whilst increasing the pipeline stage in the filter for higher speeds. Using the delayed LMS (DLMS) algorithm, fine-grained pipelined FPGA implementations using both the direct form (DF) and the transposed form (TF) are considered and compared. It is shown that the direct form LMS filter utilizes the FPGA resources more efficiently thereby allowing a 120 MHz sampling rate.

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Synthesis of free standing conducting polypyrrole film using room temperature melt as the electrolyte is reported. We also report variation in the contribution of ionic conductance with temperature of the polymer film by four probe method and electrochemical properties like diffusion coefficient and ionic mobility of AlCl-4 doped polypyrrole film. An attempt has been made to arrive at the stability of charge carrier concentration over a temperature range of 295 to 350 K under vacuum. The film was characterized by optical techniques and scanning electron micrography.

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This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.