AIMC Topic:
Computer Simulation

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Guiding Neuroevolution with Structural Objectives.

Evolutionary computation Feb 15, 2019
The structure and performance of neural networks are intimately connected, and by use of evolutionary algorithms, neural network structures optimally adapted to a given task can be explored. Guiding such neuroevolution with additional objectives rela...
Humans Neural Networks, Computer Algorithms Computer Simulation Biological Evolution
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Emergence of cognitive priming and structure building from the hierarchical interaction of canonical microcircuit models.

Biological cybernetics Feb 14, 2019
The concept of connectionism states that higher cognitive functions emerge from the interaction of many simple elements. Accordingly, research on canonical microcircuits conceptualizes findings on fundamental neuroanatomical circuits as well as recur...
Brain Computer Simulation Cognition Animals Humans Models, Neurological Neural Networks, Computer
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Gated Orthogonal Recurrent Units: On Learning to Forget.

Neural computation Feb 14, 2019
We present a novel recurrent neural network (RNN)-based model that combines the remembering ability of unitary evolution RNNs with the ability of gated RNNs to effectively forget redundant or irrelevant information in its memory. We achieve this by e...
Logic Memory Neural Networks, Computer Language Computer Simulation Learning Humans
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Estimating Scale-Invariant Future in Continuous Time.

Neural computation Feb 14, 2019
Natural learners must compute an estimate of future outcomes that follow from a stimulus in continuous time. Widely used reinforcement learning algorithms discretize continuous time and estimate either transition functions from one step to the next (...
Machine Learning Brain Time Perception Anticipation, Psychological Animals Models, Psychological Humans Models, Neurological Computer Simulation Time Decision Making Reinforcement, Psychology Memory
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Deep learning and process understanding for data-driven Earth system science.

Nature Feb 13, 2019
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, ...
Pattern Recognition, Automated Geographic Mapping Knowledge Weather Seasons Facial Recognition Earth Sciences Regression, Psychology Translating Uncertainty Reproducibility of Results Spatio-Temporal Analysis Big Data Time Factors Deep Learning Forecasting Computer Simulation Female Humans
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Improved Convolutional Pose Machines for Human Pose Estimation Using Image Sensor Data.

Sensors (Basel, Switzerland) Feb 10, 2019
In recent years, increasing human data comes from image sensors. In this paper, a novel approach combining convolutional pose machines (CPMs) with GoogLeNet is proposed for human pose estimation using image sensor data. The first stage of the CPMs di...
Posture Human Activities Humans Algorithms Computer Simulation Neural Networks, Computer Image Processing, Computer-Assisted
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Adaptive Discrete-Time Flight Control Using Disturbance Observer and Neural Networks.

IEEE transactions on neural networks and learning systems Feb 8, 2019
This paper studies the adaptive neural control (ANC)-based tracking problem for discrete-time nonlinear dynamics of an unmanned aerial vehicle subject to system uncertainties, bounded time-varying disturbances, and input saturation by using a discret...
Time Factors Algorithms Computer Simulation Neural Networks, Computer
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Finite-Time Convergence Adaptive Neural Network Control for Nonlinear Servo Systems.

IEEE transactions on cybernetics Feb 7, 2019
Although adaptive control design with function approximators, for example, neural networks (NNs) and fuzzy logic systems, has been studied for various nonlinear systems, the classical adaptive laws derived based on the gradient descent algorithm with...
Friction Feedback Nonlinear Dynamics Algorithms Computer Simulation Neural Networks, Computer
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Stability analysis of Cohen-Grossberg neural networks of neutral-type: Multiple delays case.

Neural networks : the official journal of the International Neural Network Society Feb 6, 2019
The essential purpose of this work is to conduct an investigation into stability problem for the class of neutral-type Cohen-Grossberg neural networks including multiple time delays in states and multiple neutral delays in time derivative of states. ...
Computer Simulation Neural Networks, Computer Time Factors Algorithms Models, Theoretical
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Optimal adaptive control of drug dosing using integral reinforcement learning.

Mathematical biosciences Feb 5, 2019
In this paper, a reinforcement learning (RL)-based optimal adaptive control approach is proposed for the continuous infusion of a sedative drug to maintain a required level of sedation. To illustrate the proposed method, we use the common anesthetic ...
Humans Machine Learning Anesthetics, Intravenous Drug Dosage Calculations Infusions, Parenteral Propofol Models, Biological Computer Simulation
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