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In this paper, a multi — factor prediction model based on Radical Basis Function(RBF) neural network is proposed to accurately predict the temperature of rolling bearing. According to the factors that affect the rolling bearing, including load, speed, vibration, displacement, bearing temperature and ambient temperature, the working temperature of the rolling bearing is predicted by combining the historical...
Although electromyography (EMG) signals and interaction force have been widely used in patient cooperative or interactive training, the conventional EMG based control usually breaks the process into a patient-driven phase and a separate passive phase, which is not desirable. In this research, an active interaction controller based on motion recognition and adaptive impedance control is proposed and...
Electrocardiography (ECG) is a transthoracic interpretation of the electrical activity of the human's heart over time captured and is highly irregular, random, and variable from person to person. Recently, the literature has revealed that this kind of signal is, in fact, chaotic. Because of people's ECGs are extremely hard to be artificially duplicated, this paper intends to investigate the way of...
Fed-batch processes are inherently difficult to model owing to non-steady-state operation, small-sample condition, instinct time-variation and batch-to-batch variation caused by drifting. Furthermore, when the process switches to different operation phrases, global learning modeling methods would suffer poor performance due to the negative impact of overdue training samples. In this paper, a k nearest...
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