In plastic neuronal networks, the synaptic strengths are adapted to the neuronal activity. Specifically, spike-timing-dependent plasticity (STDP) is a fundamental mechanism that modifies the synaptic strengths based on the relative timing of pre- and...
The multistable behavior of neural networks is actively being studied as a landmark of ongoing cerebral activity, reported in both functional Magnetic Resonance Imaging (fMRI) and electro- or magnetoencephalography recordings. This consists of a cont...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
In heart failure patients, hemodynamics can be regulated by therapeutic drugs. Although the cardiovascular responses to these drugs usually include nonlinearity and drug interactions, it is difficult to identify the characteristics of the dynamics un...
IEEE transactions on neural networks and learning systems
Jun 1, 2018
In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control track...
This paper evaluated the characteristics of interplant water networks along with superstructure models of such networks coordinated with intermediate pools, with the latter being assessed via nonlinear programming tools. To overcome the inherent diff...
Using an electrically coupled chain of Hindmarsh-Rose neural models, we analytically derived the nonlinearly coupled complex Ginzburg-Landau equations. This is realized by superimposing the lower and upper cutoff modes of wave propagation and by empl...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
As the bioinformatics field grows, it must keep pace not only with new data but with new algorithms. Here we contribute a thorough analysis of 13 state-of-the-art, commonly used machine learning algorithms on a set of 165 publicly available classific...
The research of this paper works out the attitude and position control of the flapping wing micro aerial vehicle (FWMAV). Neural network control with full state and output feedback are designed to deal with uncertainties in this complex nonlinear FWM...
Water science and technology : a journal of the International Association on Water Pollution Research
Aug 1, 2017
Runoff prediction, as a nonlinear and complex process, is essential for designing canals, water management and planning, flood control and predicting soil erosion. There are a number of techniques for runoff prediction based on the hydro-meteorologic...
IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Jul 1, 2017
In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynam...
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