IEEE transactions on neural networks and learning systems
May 1, 2015
Diffuse optical tomography (DOT) reconstructs 3-D tomographic images of brain activities from observations by near-infrared spectroscopy (NIRS) that is formulated as an ill-posed inverse problem. This brief presents a method for NIRS DOT based on a h...
IEEE transactions on neural networks and learning systems
May 1, 2015
Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multiinput multioutput uncertain systems. The controllers incorporate a novel variable-structure radial basis function (RBF) network as the ...
IEEE transactions on neural networks and learning systems
May 1, 2015
The use of domain knowledge in learning systems is expected to improve learning efficiency and reduce model complexity. However, due to the incompatibility with knowledge structure of the learning systems and real-time exploratory nature of reinforce...
Protein-related changes associated with the development of human brain gliomas are of increasing interest in modern neuro-oncology. It is due to the fact that they might make some of these tumors highly aggressive and difficult to treat. This paper p...
Guang pu xue yu guang pu fen xi = Guang pu
Apr 1, 2015
Adaptive de-noising algorithm is proposed based on transmission spectrum and absorption spectrum of near infrared. Near infrared transmission spectrum and absorption spectrum collected synchronously are decomposed into intrinsic mode functions by ens...
IEEE transactions on biomedical circuits and systems
Apr 1, 2015
Neuromorphic circuits are designed and simulated to emulate the role of astrocytes in phase synchronization of neuronal activity. We emulate, to a first order, the ability of slow inward currents (SICs) evoked by the astrocyte, acting on extrasynapti...
Reliable signal propagation across distributed brain areas is an essential requirement for cognitive function, and it has been investigated extensively in computational studies where feed-forward network (FFN) is taken as a generic model. But it is s...
IEEE transactions on neural networks and learning systems
Apr 1, 2015
This paper develops and validates a comprehensive and universally applicable computational concept for solving nonlinear differential equations (NDEs) through a neurocomputing concept based on cellular neural networks (CNNs). High-precision, stabilit...
IEEE transactions on neural networks and learning systems
Apr 1, 2015
This paper investigates the problems of impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks (DDNNs). Two types of DDNNs with stabilizing impulses are studied. By introducing the time-varying Lyapunov functio...
IEEE transactions on neural networks and learning systems
Apr 1, 2015
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly ...
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