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Recently the Runge-Kutta neural network (RKNN) in series-parallel configuration for identification of ordinary differential equation (ODE) was introduced. The neural network is constructed according to the Runge-Kutta approximation method whereby a precise estimate of the changing rates of the system states is possible. In this contribution we extend the approach of to a general state space representation...
A tool for discovery of gait anomalies of elderly from motion sensor data is proposed. The gait of the user is captured with the motion capture system, which consists of tags attached to the body and sensors situated in the apartment. Position of the tags is acquired by the sensors and the resulting time series of position coordinates are analyzed with dynamic time warping and machine learning algorithms...
Ensemble methods represent an approach to combine a set of models, each capable of solving a given task, but which together produce a composite global model whose accuracy and robustness exceeds that of the individual models. Ensembles of neural networks have traditionally been applied to machine learning and pattern recognition but more recently have been applied to forecasting of time series data...
This paper presents a method based on classification techniques for automatic fault diagnosis of rolling element bearings. Experimental results achieved on vibration signals collected by an accelerometer on an experimental test rig show that the method can automatically detect different types of faults. Furthermore, the method is able, once trained on an appropriate representative set of basic faults,...
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