In this paper, the design and experimental research of a broadband power amplifier is presented. This device is designed for using in 5G network base stations. Authors had declared a gain at level of more than 11 dB a...
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Continuous-time (CT) modeling has proven to provide improved sample efficiency and interpretability in learning the dynamical behavior of physical systems compared to discrete-time (DT) models. However, even with nume...
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The electromagnetic interference (EMI) problem caused by power electronic switching devices and pulse width modulation (PWM) affects the normal operation of the motor drive system. In this paper, a random PWM based on...
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The research conducted for this work has focused on the design and implementation of resilient fractional-order fuzzy integral tilt derivative with filter (FOF-ITDF) controller for renewable-dominated hybrid power sys...
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Power electronic switching devices and pulse width modulation (PWM) not only improves the performance of motor drive systems, but also brings about common-mode voltage (CMV) issues, that challenging the normal operati...
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In the noisy intermediate-scale quantum (NISQ) era, the capabilities of variational quantum algorithms are greatly constrained due to a limited number of qubits and the shallow depth of quantum circuits. We may view t...
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In the noisy intermediate-scale quantum (NISQ) era, the capabilities of variational quantum algorithms are greatly constrained due to a limited number of qubits and the shallow depth of quantum circuits. We may view these variational quantum algorithms as weak learners in supervised learning. Ensemble methods are general approaches to combining weak learners to construct a strong one in machine learning. In this paper, by focusing on classification, we theoretically establish and numerically verify a learning guarantee for quantum adaptive boosting (AdaBoost). The supervised-learning risk bound describes how the prediction error of quantum AdaBoost on binary classification decreases as the number of boosting rounds and sample size increase. We further empirically demonstrate the advantages of quantum AdaBoost by focusing on a 4-class classification. The quantum AdaBoost not only outperforms several other ensemble methods, but in the presence of noise it can also surpass the ideally noiseless but unboosted primitive classifier after only a few boosting rounds. Our work indicates that in the current NISQ era, introducing appropriate ensemble methods is particularly valuable in improving the performance of quantum machine learning algorithms.
In recent years, wide bandgap semiconductor devices such as silicon carbide (SiC) and gallium nitride (GaN) have been increasingly applied in electric drive systems, effectively enhancing system power density. However...
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As power electronics technology continues to advance, the prevalence of switching quantity interface circuits has grown in diverse domains, encompassing industrial production and everyday civilian applications. An ana...
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Recent advances in physiological human motor control research indicate that human endpoint stiffness magnitude increases linearly with grasp force. Based on these findings, a scheme was proposed in this paper to integ...
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The trajectory guidance and attitude control of Mars lander is a key point in Mars pinpoint landing *** land precisely and efficiently at the target point,an attitude-trajectory coupled control methodology is designed...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
The trajectory guidance and attitude control of Mars lander is a key point in Mars pinpoint landing *** land precisely and efficiently at the target point,an attitude-trajectory coupled control methodology is designed using nonlinear model predictive control(NMPC) in this *** advantage is that it can optimize both trajectory and attitude with online *** addition,it can deal with various physical *** achieve this autonomous control algorithm,a complex dynamics model coupled with the translational and rotational motions of the lander is ***,some physical constraints such as sight-line constraint are ***,a quadratic cost function is designed to minimize the *** simulations verify the feasibility of this autonomous control *** details are presented to demonstrate the effectiveness of the proposed algorithm.
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