Facchini L, Betti M, Biagini P (2014) Neural network based modal identification of structural systems through output- only measurement. Comput Struct 138(1):183-194Facchini, L., M. Betti, and P. Biagini, ''Neura
which is not achieved with current neural dynamic models as they are learned without considering behavior. We develop preferential subspace identification (PSID), which is an algorithm that models neural activity while dissociating and prioritizing its behaviorally relevant dynamics. Modeling data in two ...
A Hybrid Subspace-RNN based approach for Modeling of Non-Linear Batch Processes compares an Elman RNN to a hybrid model which combines a feedforward neural network with NARX structure with subspace-identified state space model (Chandrasekar et al., 2023). The results from this paper are consisten...
2.1 Radial Basis Function Neural Network Adaptive Hierarchical Sliding Mode Controller The Controller for a tendon-driven manipulator is designed using the design principles of hierarchical sliding mode control as described in Ref. [34]. To achieve this, the dynamic model of the system is divided in...
M. Large-scale dynamic modeling of task-fMRI signals via subspace system identification. J. Neural Eng. 15, 066016 (2018). PubMed Google Scholar Braun, U. et al. Brain state stability during working memory is explained by network control theory, modulated by dopamine D1/D2 receptor ...
Tracking control of tendon-driven manipulators has become a prevalent research area. However, the existence of flexible elastic tendons generates substantial residual vibrations, resulting in difficulties for trajectory tracking control of the manipulato
In each subspace, we check the number of optimal and non-optimal network samples. Then, we take the union of all optimal subspaces (those that contain more optimal networks than sub-optimal networks) to be the overall optimal region for the classifier. We then test the classifier on the ...
4.1 Example Case with a Shallow Neural Network 让我们首先考虑一个只有一个隐含层的标准神经网络(NN)体系结构。为简单起见,我们假设输入空间是由m维实向量构成的。因此 。隐藏层 学习了将一个样本映射到一个新的D维表征的函数 ,且其参数为一个矩阵向量对 ...
Collection of recent methods on (deep) neural network compression and acceleration. - MingSun-Tse/Efficient-Deep-Learning
Liu et al. proposed a deep neural network (DNN) method for structural modal identification that uses the independence of modal responses, but it also needs priori information of the model order [50]. Liu et al. proposed a method that combines machine learning and stochastic subspace for ...