AIMC Topic: Learning

Clear Filters Showing 1211 to 1220 of 1476 articles

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

Computational intelligence and neuroscience May 21, 2015
Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonpara...
Male Learning Decision Making Likelihood Functions Female Humans Base Sequence Breast Neoplasms Machine Learning Databases, Factual
View on PubMed DOI

Learning Slowness in a Sparse Model of Invariant Feature Detection.

Neural computation May 14, 2015
Primary visual cortical complex cells are thought to serve as invariant feature detectors and to provide input to higher cortical areas. We propose a single model for learning the connectivity required by complex cells that integrates two factors tha...
Neurons Markov Chains Visual Perception Machine Learning Visual Cortex Learning Eye Movements Humans Time Factors Models, Neurological
View on PubMed DOI

A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data.

Neural computation May 14, 2015
Neural network models of early sensory processing typically reduce the dimensionality of streaming input data. Such networks learn the principal subspace, in the sense of principal component analysis, by adjusting synaptic weights according to activi...
Models, Neurological Principal Component Analysis Neural Networks, Computer Neurons Linear Models Algorithms Learning
View on PubMed DOI

Perception Evolution Network Based on Cognition Deepening Model--Adapting to the Emergence of New Sensory Receptor.

IEEE transactions on neural networks and learning systems Apr 28, 2015
The proposed perception evolution network (PEN) is a biologically inspired neural network model for unsupervised learning and online incremental learning. It is able to automatically learn suitable prototypes from learning data in an incremental way,...
Models, Theoretical Neural Networks, Computer Humans Perception Learning Animals Sensory Receptor Cells Cognition Adaptation, Biological
View on PubMed DOI

High-Density Electromyography and Motor Skill Learning for Robust Long-Term Control of a 7-DoF Robot Arm.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 31, 2015
Myoelectric control offers a direct interface between human intent and various robotic applications through recorded muscle activity. Traditional control schemes realize this interface through direct mapping or pattern recognition techniques. The for...
Humans Robotics Biofeedback, Psychology Electromyography Movement Muscle Contraction Adult Man-Machine Systems Motor Skills Male Algorithms Computer Systems Learning Muscle, Skeletal Young Adult
View on PubMed DOI

Timescale separation in recurrent neural networks.

Neural computation Mar 31, 2015
Supervised learning in recurrent neural networks involves two processes: the neuron activity from which gradients are estimated and the process on connection parameters induced by these measurements. A problem such algorithms must address is how to b...
Artificial Intelligence Algorithms Computer Simulation Models, Neurological Neurons Learning Animals Humans Neural Networks, Computer
View on PubMed DOI

Interactive effects of explicit emergent structure: a major challenge for cognitive computational modeling.

Topics in cognitive science Mar 31, 2015
David Marr's (1982) three-level analysis of computational cognition argues for three distinct levels of cognitive information processing-namely, the computational, representational, and implementational levels. But Marr's levels are-and were meant to...
Cognition Concept Formation Humans Neural Networks, Computer Learning
View on PubMed DOI

Using Functional Electrical Stimulation Mediated by Iterative Learning Control and Robotics to Improve Arm Movement for People With Multiple Sclerosis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 24, 2015
Few interventions address multiple sclerosis (MS) arm dysfunction but robotics and functional electrical stimulation (FES) appear promising. This paper investigates the feasibility of combining FES with passive robotic support during virtual reality ...
Female Reproducibility of Results Adult Middle Aged Humans Algorithms Learning Feasibility Studies Arm Multiple Sclerosis Electric Stimulation Treatment Outcome Follow-Up Studies Robotics Movement Electric Stimulation Therapy
View on PubMed DOI

A spiking neural network based on the basal ganglia functional anatomy.

Neural networks : the official journal of the International Neural Network Society Mar 24, 2015
We introduce a spiking neural network of the basal ganglia capable of learning stimulus-action associations. We model learning in the three major basal ganglia pathways, direct, indirect and hyperdirect, by spike time dependent learning and consideri...
Learning Models, Neurological Dopamine Basal Ganglia Neural Pathways Thalamus Humans Neural Networks, Computer Machine Learning
View on PubMed DOI

Facilitatory effects of anti-spastic medication on robotic locomotor training in people with chronic incomplete spinal cord injury.

Journal of neuroengineering and rehabilitation Mar 20, 2015
BACKGROUND: The objective of this study was to investigate whether an anti-spasticity medication can facilitate the effects of robotic locomotor treadmill training (LTT) to improve gait function in people with incomplete spinal cord injury (SCI).
Male Muscle Spasticity Middle Aged Treatment Outcome Gait Learning Isometric Contraction Muscle, Skeletal Clonidine Range of Motion, Articular Female Aged Muscle Relaxants, Central Muscle Strength Locomotion Humans Robotics Spinal Cord Injuries Adult Walking Biomechanical Phenomena
View on PubMed DOI
Popular Topics
Recent Journals