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Total dose tests of several bipolar linear devices show sensitivity to both dose rate and bias during exposure. All devices exhibited Enhanced Low Dose Rate Sensitivity (ELDRS). An accelerated ELDRS test method for three different...
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Total dose tests of several bipolar linear devices show sensitivity to both dose rate and bias during exposure. All devices exhibited Enhanced Low Dose Rate Sensitivity (ELDRS). An accelerated ELDRS test method for three different devices demonstrate results similar to tests at low dose rate. Behavior and critical parameters from these tests are compared and discussed.
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The Educational Technology team (EdTech team) at one of the largest academic medical centres in the USA was tasked with the responsibility to oversee university’s migration from one learning management’s system (LMS) to another....
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The Educational Technology team (EdTech team) at one of the largest academic medical centres in the USA was tasked with the responsibility to oversee university’s migration from one learning management’s system (LMS) to another. This included the implementation and adoption of a new learning management system in a concise timeline of 5 months. This paper will describe the development process, critical components of the transition, the training plan, support needs, and methods to obtain faculty adoption. According to 2017 research by Rucker & Frass: “By investigating LMS migrations at other institutions, administrators and IT professionals can determine the best type of training and support to provide faculty members” [7, p260]. By sharing their experiences, the EdTech team will contribute to the body of research allowing for further development of LMS migration framework.
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There are inherent disadvantages in traditional BP neural network. First, the error of training drops slowly. Second, the adjustment time is too long because of too many iteration steps. Last but not least it even easily falls int...
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There are inherent disadvantages in traditional BP neural network. First, the error of training drops slowly. Second, the adjustment time is too long because of too many iteration steps. Last but not least it even easily falls into local minimum and is hardly able to extricate itself, which leads to low accuracy of diagnosis. Therefore, a new BP network method optimized by genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithm is proposed. In this method, the BP network's structure is optimized by GA. Then LM algorithm is used to train the BP network. The training result could diagnose the faults of analog circuits, which is able to overcome the inherent disadvantages of traditional BP network. Several simulation and experimental results are presented, demonstrating the effectiveness and applicability of the developed method.
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We propose a new NDA-LMS algorithm for joint equalization and carrier recovery. Our analysis shows that NDA-LMS algorithm without any carrier phase estimation circuit can jointly achieve bit error rate (BER) of 10~(-3) with less t...
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We propose a new NDA-LMS algorithm for joint equalization and carrier recovery. Our analysis shows that NDA-LMS algorithm without any carrier phase estimation circuit can jointly achieve bit error rate (BER) of 10~(-3) with less than 2.8dB OSNR penalty for ΔvT is 10~(-4) with 150Km impairment.
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This paper describes a simple approach to generate an efficient hybrid word/Part-of-Arabic-Word (PAW) Language Model (LM). More precisely, less frequent words in a full word vocabulary are decomposed into PAWs. The resulted PAWs a...
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This paper describes a simple approach to generate an efficient hybrid word/Part-of-Arabic-Word (PAW) Language Model (LM). More precisely, less frequent words in a full word vocabulary are decomposed into PAWs. The resulted PAWs are incorporated with the most frequent words to generate a hybrid word-PAW vocabulary which is used to estimate a hybrid flat n-gram statistical language model. For comparison purposes, language models with full PAW decomposition of the word vocabulary are generated. To assess the quality of the three types of LMs (i.e. full word, hybrid word/PAW and full PAW LMs), evaluation experiments are conducted under three different tasks using two benchmarking databases, namely Maurdor and Khatt. Results in terms of word error rate show that systems using the full PAW and the proposed hybrid LMs perform equally the same, and both of them, systematically, outperform systems using word LMs. However, systems using hybrid LMs require less memory than those using full PAW LMs.
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To the best of our knowledge, this study represents the proposal using the dynamic least mean square (DLMS) algorithm to reduce the computation load of LMS. Moreover, three regions of impulse response of line echo path are also pr...
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To the best of our knowledge, this study represents the proposal using the dynamic least mean square (DLMS) algorithm to reduce the computation load of LMS. Moreover, three regions of impulse response of line echo path are also proposed to analyze the redundant coefficients. Using the DLMS method, redundant coefficients can be detected and grouped, thereby automatically reducing computation. We employed line echo cancellation (LEC) to evaluate the performance of DLMS. The pure-delay and overlong regions of impulse response of line echo path are grouped and the associated computation load is reduced. The experimental results confirm the excellent performance of DLMS achieving a 35% savings in computation. Moreover, the quality echo return loss enhancement (ERLE) of DLMS also maintains at a level nearly equal to LMS.
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The article proposes a variable step-size algorithm of LMS adaptive algorithm by using smoothing function to govern adaptation of the step-size value. The function performs based on squared error autocorrelation criterion. This ap...
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The article proposes a variable step-size algorithm of LMS adaptive algorithm by using smoothing function to govern adaptation of the step-size value. The function performs based on squared error autocorrelation criterion. This approach purposes to produce a large value of step size for fast convergent speed in transient state and a small value of step size for low mean square deviation (MSD) level in steady state of the algorithm. Furthermore, the simulation results have shown that performances of the proposed algorithm have been very well over other algorithms under the same conditional test.
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Various structural measures against vibration and noise were taken in a training ship, Oshima Maru. However, an unpleasant sound persisted in the mess hall, where crews take their breaks. In order to reduce the noise, active contr...
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Various structural measures against vibration and noise were taken in a training ship, Oshima Maru. However, an unpleasant sound persisted in the mess hall, where crews take their breaks. In order to reduce the noise, active controllers were investigated. Some of them were preconditioned using the inverse of the plant because their convergence rates are limited by the dynamics and coupling within the plant response. The algorithms were compared under the same conditions to investigate differences in their properties and also corrected to satisfy the causality of their update processes. Simulations for a control system were introduced using plant responses measured from a loudspeaker to a microphone in the mess hall inside Oshima Maru. After investigating the convergence speed in various gradient descent adaptation algorithms, the results were integrated with the actual plant response and applied to the active control of ship interior noise. It was also shown that the although preconditioned LMS algorithm converges dramatically faster than the ordinary gradient descent adaptation algorithms with an accurate plant model, its convergence rate is still sensitive to the autocorrelation and cross-correlation properties of the reference signals.
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摘要 :
Various structural measures against vibration and noise were taken in a training ship, Oshima Maru. However, an unpleasant sound persisted in the mess hall, where crews take their breaks. In order to reduce the noise, active contr...
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Various structural measures against vibration and noise were taken in a training ship, Oshima Maru. However, an unpleasant sound persisted in the mess hall, where crews take their breaks. In order to reduce the noise, active controllers were investigated. Some of them were preconditioned using the inverse of the plant because their convergence rates are limited by the dynamics and coupling within the plant response. The algorithms were compared under the same conditions to investigate differences in their properties and also corrected to satisfy the causality of their update processes. Simulations for a control system were introduced using plant responses measured from a loudspeaker to a microphone in the mess hall inside Oshima Maru. After investigating the convergence speed in various gradient descent adaptation algorithms, the results were integrated with the actual plant response and applied to the active control of ship interior noise. It was also shown that the although preconditioned LMS algorithm converges dramatically faster than the ordinary gradient descent adaptation algorithms with an accurate plant model, its convergence rate is still sensitive to the autocorrelation and cross-correlation properties of the reference signals.
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OFDM PHY has been selected as North American DSRC standard (IEEE 802.11p). In this paper, we present a robust inner receiver suitable for DSRC communications, whose core is composed by a synchronizer, a one-tap frequency domain eq...
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OFDM PHY has been selected as North American DSRC standard (IEEE 802.11p). In this paper, we present a robust inner receiver suitable for DSRC communications, whose core is composed by a synchronizer, a one-tap frequency domain equalizer (FDE) and a pilot-based phase estimator. The equalizer uses least-mean-square (LMS) algorithm to track not only the variation of the DSRC channel in 5.9GHz band but also the residual frequency/phase errors that are not yet being corrected by the synchronizer device. In order to keep the LMS equalizer working well, we utilize a pilot-based phase estimator to help estimate the variation and the errors. The simulation results indicate that our proposed inner receiver works fairly well for two DSRC channel models.
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