AIMC Topic: Neural Networks, Computer

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Adaptive Neural Stabilizing Controller for a Class of Mismatched Uncertain Nonlinear Systems by State and Output Feedback.

IEEE transactions on cybernetics
In this paper, first, an adaptive neural network (NN) state-feedback controller for a class of nonlinear systems with mismatched uncertainties is proposed. By using a radial basis function NN (RBFNN), a bound of unknown nonlinear functions is approxi...

Adaptive Neural Control of Nonaffine Systems With Unknown Control Coefficient and Nonsmooth Actuator Nonlinearities.

IEEE transactions on neural networks and learning systems
This brief considers the asymptotic tracking problem for a class of high-order nonaffine nonlinear dynamical systems with nonsmooth actuator nonlinearities. A novel transformation approach is proposed, which is able to systematically transfer the ori...

Globally Stable Adaptive Backstepping Neural Network Control for Uncertain Strict-Feedback Systems With Tracking Accuracy Known a Priori.

IEEE transactions on neural networks and learning systems
This paper addresses the problem of globally stable direct adaptive backstepping neural network (NN) tracking control design for a class of uncertain strict-feedback systems under the assumption that the accuracy of the ultimate tracking error is giv...

Short-term plasticity based network model of place cells dynamics.

Hippocampus
Rodent hippocampus exhibits strikingly different regimes of population activity in different behavioral states. During locomotion, hippocampal activity oscillates at theta frequency (5-12 Hz) and cells fire at specific locations in the environment, t...

A hybrid artificial neural network and particle swarm optimization for prediction of removal of hazardous dye brilliant green from aqueous solution using zinc sulfide nanoparticle loaded on activated carbon.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In the present study, zinc sulfide nanoparticle loaded on activated carbon (ZnS-NP-AC) simply was synthesized in the presence of ultrasound and characterized using different techniques such as SEM and BET analysis. Then, this material was used for br...

Development of early-warning protocol for predicting chlorophyll-a concentration using machine learning models in freshwater and estuarine reservoirs, Korea.

The Science of the total environment
Chlorophyll-a (Chl-a) is a direct indicator used to evaluate the ecological state of a waterbody, such as algal blooms that degrade the water quality in lakes, reservoirs and estuaries. In this study, artificial neural network (ANN) and support vecto...

Synchronization among neuronal pools without common inputs: in vivo study.

Brain structure & function
Periodic synchronization of activity among neuronal pools has been related to substantial neural processes and information throughput in the neocortical network. However, the mechanisms of generating such periodic synchronization among distributed po...

Human-Like Behavior Generation Based on Head-Arms Model for Robot Tracking External Targets and Body Parts.

IEEE transactions on cybernetics
Facing and pointing toward moving targets is a usual and natural behavior in daily life. Social robots should be able to display such coordinated behaviors in order to interact naturally with people. For instance, a robot should be able to point and ...

An Experimentation Platform for On-Chip Integration of Analog Neural Networks: A Pathway to Trusted and Robust Analog/RF ICs.

IEEE transactions on neural networks and learning systems
We discuss the design of an experimentation platform intended for prototyping low-cost analog neural networks for on-chip integration with analog/RF circuits. The objective of such integration is to support various tasks, such as self-test, self-tuni...

Understanding migraine using dynamic network biomarkers.

Cephalalgia : an international journal of headache
BACKGROUND: Mathematical modeling approaches are becoming ever more established in clinical neuroscience. They provide insight that is key to understanding complex interactions of network phenomena, in general, and interactions within the migraine-ge...