AIMC Topic: Computer Simulation
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Variable neural adaptive robust control: a switched system approach.
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 ...
Self-organizing neural networks integrating domain knowledge and reinforcement learning.
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...
Advanced Insulin Bolus Advisor Based on Run-To-Run Control and Case-Based Reasoning.
IEEE journal of biomedical and health informatics
May 1, 2015
This paper presents an advanced insulin bolus advisor for people with diabetes on multiple daily injections or insulin pump therapy. The proposed system, which runs on a smartphone, keeps the simplicity of a standard bolus calculator while enhancing ...
Video-based peer feedback through social networking for robotic surgery simulation: a multicenter randomized controlled trial.
Annals of surgery
May 1, 2015
OBJECTIVE: To examine the feasibility and outcomes of video-based peer feedback through social networking to facilitate robotic surgical skill acquisition.
Intrinsic excitability state of local neuronal population modulates signal propagation in feed-forward neural networks.
Chaos (Woodbury, N.Y.)
Apr 1, 2015
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...
A universal concept based on cellular neural networks for ultrafast and flexible solving of differential equations.
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...
Impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks.
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...
Adaptive optimal control of highly dissipative nonlinear spatially distributed processes with neuro-dynamic programming.
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 ...
Quaternion-valued echo state networks.
IEEE transactions on neural networks and learning systems
Apr 1, 2015
Quaternion-valued echo state networks (QESNs) are introduced to cater for 3-D and 4-D processes, such as those observed in the context of renewable energy (3-D wind modeling) and human centered computing (3-D inertial body sensors). The introduction ...
Robotic assistance with needle guidance.
British journal of anaesthesia
Apr 1, 2015
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