28 resultados para 090699 Electrical and Electronic Engineering not elsewhere classified

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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The ability of millimetre wave and terahertz systems to penetrate clothing is well known. The fact that the transmission of clothing and the reflectivity of the body vary as a function of frequency is less so. Several instruments have now been developed to exploit this capability. The choice of operating frequency, however, has often been associated with the maturity and the cost of the enabling technology rather than a sound systems engineering approach. Top level user and systems requirements have been derived to inform the development of design concepts. Emerging micro and nano technology concepts have been reviewed and we have demonstrated how these can be evaluated against these requirements by simulation using OpenFx. Openfx is an open source suite of 3D tools for modeling, animation and visualization which has been modified for use at millimeter waves. © 2012 SPIE.

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In this paper, we propose for the first time, an analytical model for short channel effects in nanoscale source/drain extension region engineered double gate (DG) SOI MOSFETs. The impact of (i) lateral source/drain doping gradient (d), (ii) spacer width (s), (iii) spacer to doping gradient ratio (s/d) and (iv) silicon film thickness (T-si), on short channel effects - threshold voltage (V-th) and subthreshold slope (S), on-current (I-on), off-current (I-on) and I-on/I-off is extensively analysed by using the analytical model and 2D device simulations. The results of the analytical model confirm well with simulated data over the entire range of spacer widths, doping gradients and effective channel lengths. Results show that lateral source/drain doping gradient along with spacer width can not only effectively control short channel effects, thus presenting low off-current, but can also be optimised to achieve high values of on-currents. The present work provides valuable design insights in the performance of nanoscale DG Sol devices with optimal source/drain engineering and serves as a tool to optimise important device and technological parameters for 65 nm technology node and below. (c) 2006 Elsevier Ltd. All rights reserved.

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This is the first paper to describe performance assessment of triple and double gate FinFETs for High Performance (HP), Low Operating Power (LOP) and Low Standby Power (LSTP) logic technologies is investigated. The impact of gate work-function, spacer width, lateral source/drain doping gradient, fin aspect ratio, fin thickness on device performance, has been analysed in detail and guidelines are presented to meet ITRS specification at 65 and 45 nm nodes. Optimal design of lateral source/drain doping profile can not only effectively control short channel effects, yielding low off-current, but also achieve low values of intrinsic gate delay.

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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 paper considers invariant texture analysis. Texture analysis approaches whose performances are not affected by translation, rotation, affine, and perspective transform are addressed. Existing invariant texture analysis algorithms are carefully studied and classified into three categories: statistical methods, model based methods, and structural methods. The importance of invariant texture analysis is presented first. Each approach is reviewed according to its classification, and its merits and drawbacks are outlined. The focus of possible future work is also suggested.

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This paper presents a new method for complex power flow tracing that can be used for allocating the transmission loss to loads or generators. Two algorithms for upstream tracing (UST) and downstream tracing (DST) of the complex power are introduced. UST algorithm traces the complex power extracted by loads back to source nodes and assigns a fraction of the complex power flow through each line to each load. DST algorithm traces the output of the generators down to the sink nodes determining the contributions of each generator to the complex power flow and losses through each line. While doing so, active- and reactive-power flows as well as complex losses are considered simultaneously, not separately as most of the available methods do. Transmission losses are taken into consideration during power flow tracing. Unbundling line losses are carried out using an equation, which has a physical basis, and considers the coupling between active- and reactive-power flows as well as the cross effects of active and reactive powers on active and reactive losses. The tracing algorithms introduced can be considered direct to a good extent, as there is no need for exhaustive search to determine the flow paths as these are determined in a systematic way during the course of tracing. Results of application of the proposed method are also presented.

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The impact of source/drain engineering on the performance of a six-transistor (6-T) static random access memory (SRAM) cell, based on 22 nm double-gate (DG) SOI MOSFETs, has been analyzed using mixed-mode simulation, for three different circuit topologies for low voltage operation. The trade-offs associated with the various conflicting requirements relating to read/write/standby operations have been evaluated comprehensively in terms of eight performance metrics, namely retention noise margin, static noise margin, static voltage/current noise margin, write-ability current, write trip voltage/current and leakage current. Optimal design parameters with gate-underlap architecture have been identified to enhance the overall SRAM performance, and the influence of parasitic source/drain resistance and supply voltage scaling has been investigated. A gate-underlap device designed with a spacer-to-straggle (s/sigma) ratio in the range 2-3 yields improved SRAM performance metrics, regardless of circuit topology. An optimal two word-line double-gate SOI 6-T SRAM cell design exhibits a high SNM similar to 162 mV, I-wr similar to 35 mu A and low I-leak similar to 70 pA at V-DD = 0.6 V, while maintaining SNM similar to 30% V-DD over the supply voltage (V-DD) range of 0.4-0.9 V.

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In this paper, by investigating the influence of source/drain extension region engineering (also known as gate-source/drain underlap) in nanoscale planar double gate (DG) SOI MOSFETs, we offer new insights into the design of future nanoscale gate-underlap DG devices to achieve ITRS projections for high performance (HP), low standby power (LSTP) and low operating power (LOP) logic technologies. The impact of high-kappa gate dielectric, silicon film thickness, together with parameters associated with the lateral source/drain doping profile, is investigated in detail. The results show that spacer width along with lateral straggle can not only effectively control short-channel effects, thus presenting low off-current in a gate underlap device, but can also be optimized to achieve lower intrinsic delay and higher on-off current ratio (I-on/I-off). Based on the investigation of on-current (I-on), off-current (I-off), I-on/I-off, intrinsic delay (tau), energy delay product and static power dissipation, we present design guidelines to select key device parameters to achieve ITRS projections. Using nominal gate lengths for different technologies, as recommended from ITRS specification, optimally designed gate-underlap DG MOSFETs with a spacer-to-straggle (s/sigma) ratio of 2.3 for HP/LOP and 3.2 for LSTP logic technologies will meet ITRS projection. However, a relatively narrow range of lateral straggle lying between 7 to 8 nm is recommended. A sensitivity analysis of intrinsic delay, on-current and off-current to important parameters allows a comparative analysis of the various design options and shows that gate workfunction appears to be the most crucial parameter in the design of DG devices for all three technologies. The impact of back gate misalignment on I-on, I-off and tau is also investigated for optimized underlap devices.

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This paper presents an optimization-based approach to the design of asymmetrical filter structures having the maximum number of return- or insertion-loss ripples in the passband such as those based upon Chebyshev function prototypes. The proposed approach. has the following advantages over the general purpose optimization techniques adopted previously such as: less frequency sampling is required, optimization is carried out with respect to the Chebyshev (or minimax) criterion, the problem of local minima does not arise, and optimization is usually only required for the passband. When implemented around an accurate circuit simulation, the method can be used to include all the effects of discontinuities, junctions, fringing, etc. to reduce the amount of tuning required in the final filter. The design of asymmetrical ridged-waveguide bandpass filters is considered as an example. Measurements on a fabricated filter confirm the accuracy of the design procedure.

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This paper presents some observations on how computer animation was used in the early years of a degree program in Electrical and Electronic Engineering to enhance the teaching of key skills and professional practice. This paper presents the results from two case studies. First, in a first year course which seeks to teach students how to manage and report on group projects in a professional way. Secondly, in a technical course on virtual reality, where the students are asked to use computer animation in a way that subliminally coerces them to come to terms with the fine detail of the mathematical principles that underlie 3D graphics, geometry, etc. as well as the most significant principles of computer architecture and software engineering. In addition, the findings reveal that by including a significant element of self and peer review processes into the assessment procedure students became more engaged with the course and achieved a deeper level of comprehension of the material in the course.

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The least-mean-fourth (LMF) algorithm is known for its fast convergence and lower steady state error, especially in sub-Gaussian noise environments. Recent work on normalised versions of the LMF algorithm has further enhanced its stability and performance in both Gaussian and sub-Gaussian noise environments. For example, the recently developed normalised LMF (XE-NLMF) algorithm is normalised by the mixed signal and error powers, and weighted by a fixed mixed-power parameter. Unfortunately, this algorithm depends on the selection of this mixing parameter. In this work, a time-varying mixed-power parameter technique is introduced to overcome this dependency. A convergence analysis, transient analysis, and steady-state behaviour of the proposed algorithm are derived and verified through simulations. An enhancement in performance is obtained through the use of this technique in two different scenarios. Moreover, the tracking analysis of the proposed algorithm is carried out in the presence of two sources of nonstationarities: (1) carrier frequency offset between transmitter and receiver and (2) random variations in the environment. Close agreement between analysis and simulation results is obtained. The results show that, unlike in the stationary case, the steady-state excess mean-square error is not a monotonically increasing function of the step size. (c) 2007 Elsevier B.V. All rights reserved.

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This study investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in the existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particular interest is the channel estimation at the relay node which imposes extra requirement for the system resources. The authors propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The soft-in-soft-out minimum mean square error (MMSE) equaliser is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm.

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Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.