AIMC Topic: Learning

Clear Filters Showing 1041 to 1050 of 1476 articles

Blind Channel and Data Estimation Using Fuzzy Logic-Empowered Opposite Learning-Based Mutant Particle Swarm Optimization.

Computational intelligence and neuroscience
Multiple-input and multiple-output (MIMO) technology is one of the latest technologies to enhance the capacity of the channel as well as the service quality of the communication system. By using the MIMO technology at the physical layer, the estimati...

Emergent neural turing machine and its visual navigation.

Neural networks : the official journal of the International Neural Network Society
Traditional Turing Machines (TMs) are symbolic whose hand-crafted representations are static and limited. Developmental Network 1 (DN-1) uses emergent representation to perform Turing Computation. But DN-1 lacks hierarchy in its internal representati...

In vitro neural networks minimise variational free energy.

Scientific reports
In this work, we address the neuronal encoding problem from a Bayesian perspective. Specifically, we ask whether neuronal responses in an in vitro neuronal network are consistent with ideal Bayesian observer responses under the free energy principle....

Cumulative inhibition in neural networks.

Cognitive processing
We show how a multi-resolution network can model the development of acuity and coarse-to-fine processing in the mammalian visual cortex. The network adapts to input statistics in an unsupervised manner, and learns a coarse-to-fine representation by u...

Optimal Synthesis of Four-Bar Linkage Path Generation through Evolutionary Computation with a Novel Constraint Handling Technique.

Computational intelligence and neuroscience
This paper presents a novel constraint handling technique for optimum path generation of four-bar linkages using evolutionary algorithms (EAs). Usually, the design problem is assigned to minimize the error between desired and obtained coupler curves ...

Testing of an assistive robot system for haptic exploration of objects.

Assistive technology : the official journal of RESNA
INTRODUCTION: When children with physical impairments cannot perform hand movements for haptic exploration, they may miss opportunities to learn the properties of objects. Assistive robots may enable them to make manipulation actions.

Sparse Representation-Based Extreme Learning Machine for Motor Imagery EEG Classification.

Computational intelligence and neuroscience
Classification of motor imagery (MI) electroencephalogram (EEG) plays a vital role in brain-computer interface (BCI) systems. Recent research has shown that nonlinear classification algorithms perform better than their linear counterparts, but most o...

The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care.

Nature medicine
Sepsis is the third leading cause of death worldwide and the main cause of mortality in hospitals, but the best treatment strategy remains uncertain. In particular, evidence suggests that current practices in the administration of intravenous fluids ...

Interactive reservoir computing for chunking information streams.

PLoS computational biology
Chunking is the process by which frequently repeated segments of temporal inputs are concatenated into single units that are easy to process. Such a process is fundamental to time-series analysis in biological and artificial information processing sy...

A little labeling goes a long way: Semi-supervised learning in infancy.

Developmental science
There is considerable evidence that labeling supports infants' object categorization. Yet in daily life, most of the category exemplars that infants encounter will remain unlabeled. Inspired by recent evidence from machine learning, we propose that i...