while significant advances have been made on the blast analysis, applications of nonlinear analysis of structures under explosion have been limited to the frames and structural behavior of bridges subjected to blast is an issue that has attracted attention of researchers in recent years. nonlinear dynamic analysis can be lead to the most accurate responses of the structure under blast but the u...

The nonlinear system becomes an area with numerous investigations over the past decades. The conventional modal analysis could not be  applied on nonlinear continuous system which makes it impossible to construct the reduced order models and obtain system response based on limited number of measurement points. Nonlinear normal modes provide a useful tool for extending modal analysis to nonlinea...

Principal component analysis (PCA) has been generalized to complex principal component analysis (CPCA), which has been widely applied to complex-valued data, two-dimensional vector fields, and complexified real data through the Hilbert transform. Nonlinear PCA (NLPCA) can also be performed using auto-associative feed-forward neural network (NN) models, which allows the extraction of nonlinear f...

Networks of living neurons exhibit diverse patterns of activity, which are always operating far from equilibrium in the mammalian central nervous system. In this study, a blocker of glutamate transporter was employed to detect if nonlinear interactions changed when extra glutamate acted as a potent neurotoxin to neural activity in hippocampus of epileptic Wistar rats. A hypothesis was made that...

Inspired by the theory of multiresolution analysis (MRA) of wavelets and artificial neural networks, a multiresolution neural network (MRNN) for approximating arbitrary nonlinear functions is proposed in this paper. MRNN consists of a scaling function neural network (SNN) and a set of sub-wavelet neural networks, in which each sub-neural network can capture the specific approximation behavior (...