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In this paper, a novel model, named double-reservoir echo state networks (DR-ESN), is proposed. DR-ESN is constructed by two reservoirs which are connected in series, thus the performance of abstracting the characteristics from the prediction task is improved. A sufficient condition is provided to ensure the stability of DR-ESN. The batch gradient method and ridge regression method are utilized to...
Since it is difficult to establish precise physical model of complex systems, time series prediction is often used to predict their health trend and running state. Aiming at online prediction, we proposed a new scheme to fix the problems of time series online prediction, which is based on LS-SVR model and incremental learning algorithm. The scheme includes two aspects. Firstly, by replacing single...
This paper mainly studies about the data processing of brain computer interface(BCI) and presents a kind of method for classifying the ECoG motor imagery tasks. Both the training and testing ECoG datasets were filtered with the frequency band of 8–30Hz according to the event-related desynchronization and synchronization(ERD/ERS) phenomenon. The features were extracted by using Common Spatial Pattern(CSP)...
In order to solve the problems of correctly identifying fault classes in fault diagnosis of analogue circuit and improve classification ability, a fault diagnosis method for analog circuits based on AdaBoost algorithm and hypersphere support vector machine (hypersphere SVM) is developed in this paper. This algorithm uses Hyper-sphere SVMs as weak learners of AdaBoost and use AdaBoost algorithm to...
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