AIMC Topic:
Learning

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Adaptive control of uncertain nonaffine nonlinear systems with input saturation using neural networks.

IEEE transactions on neural networks and learning systems Dec 19, 2014
This paper presents a tracking control methodology for a class of uncertain nonlinear systems subject to input saturation constraint and external disturbances. Unlike most previous approaches on saturated systems, which assumed affine nonlinear syste...
Neural Networks, Computer Algorithms Computer Simulation Humans Nonlinear Dynamics Adaptation, Physiological Learning Uncertainty Feedback
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Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

Neural networks : the official journal of the International Neural Network Society Dec 11, 2014
The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper....
Artificial Intelligence Algorithms Cluster Analysis Pattern Recognition, Automated Learning
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Sub-processes of motor learning revealed by a robotic manipulandum for rodents.

Behavioural brain research Nov 8, 2014
Rodent models are widely used to investigate neural changes in response to motor learning. Usually, the behavioral readout of motor learning tasks used for this purpose is restricted to a binary measure of performance (i.e. "successful" movement vs. ...
Male Rats Robotics Learning Rats, Long-Evans Motor Skills Biomechanical Phenomena Movement Animals
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Learning Stable Multilevel Dictionaries for Sparse Representations.

IEEE transactions on neural networks and learning systems Oct 16, 2014
Sparse representations using learned dictionaries are being increasingly used with success in several data processing and machine learning applications. The increasing need for learning sparse models in large-scale applications motivates the developm...
Humans Neural Networks, Computer Algorithms Cluster Analysis Pattern Recognition, Automated Computer Simulation Learning
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Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter.

IEEE transactions on neural networks and learning systems Oct 15, 2014
This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an ...
Pattern Recognition, Automated Neural Networks, Computer Algorithms Computer Systems Time Factors Learning Humans
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State-trace analysis: dissociable processes in a connectionist network?

Cognitive science Oct 12, 2014
Some argue the common practice of inferring multiple processes or systems from a dissociation is flawed (Dunn, 2003). One proposed solution is state-trace analysis (Bamber, 1979), which involves plotting, across two or more conditions of interest, pe...
Computer Simulation Learning Humans Neural Networks, Computer
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Do lemmas speak German? A verb position effect in German structural priming.

Cognitive science Oct 12, 2014
Lexicalized theories of syntax often assume that verb-structure regularities are mediated by lemmas, which abstract over variation in verb tense and aspect. German syntax seems to challenge this assumption, because verb position depends on tense and ...
Young Adult Adult Male Learning Female Adolescent Linguistics Neural Networks, Computer Language Humans
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Neural coordination can be enhanced by occasional interruption of normal firing patterns: a self-optimizing spiking neural network model.

Neural networks : the official journal of the International Neural Network Society Sep 16, 2014
The state space of a conventional Hopfield network typically exhibits many different attractors of which only a small subset satisfies constraints between neurons in a globally optimal fashion. It has recently been demonstrated that combining Hebbian...
Brain Learning Neurons Artificial Intelligence Humans Algorithms Neural Networks, Computer
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Toward a tactile language for human-robot interaction: two studies of tacton learning and performance.

Human factors Aug 28, 2014
OBJECTIVE: Two experiments were performed to investigate the feasibility for robot-to-human communication of a tactile language using a lexicon of standardized tactons (tactile icons) within a sentence.
Touch Perception Male Man-Machine Systems Adolescent Touch Female Humans Workload Robotics Task Performance and Analysis Young Adult Learning Adult
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Is extreme learning machine feasible? A theoretical assessment (part II).

IEEE transactions on neural networks and learning systems Jul 23, 2014
An extreme learning machine (ELM) can be regarded as a two-stage feed-forward neural network (FNN) learning system that randomly assigns the connections with and within hidden neurons in the first stage and tunes the connections with output neurons i...
Learning Artificial Intelligence Models, Neurological Probability Humans Neurons Algorithms Computer Simulation Neural Networks, Computer
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