A training-efficient Wiener-type neural network modeling approach for structural dynamic response prediction
Neural network techniques have been widely exploited to model structural dynamics. Among them, the continuous-time state-space neural network (CSNN) possesses great potential because of its advantage that a trained CSNN model can operate at different sampling rates without retraining. However, it has relatively low tra...