AIMC Topic: Neural Networks, Computer

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Emergence of Leadership in a Group of Autonomous Robots.

PloS one
In this paper we examine the factors contributing to the emergence of leadership in a group, and we explore the relationship between the role of the leader and the behavioural capabilities of other individuals. We use a simulation technique where a g...

A Unified Approach to Adaptive Neural Control for Nonlinear Discrete-Time Systems With Nonlinear Dead-Zone Input.

IEEE transactions on neural networks and learning systems
In this paper, an effective adaptive control approach is constructed to stabilize a class of nonlinear discrete-time systems, which contain unknown functions, unknown dead-zone input, and unknown control direction. Different from linear dead zone, th...

Networks that learn the precise timing of event sequences.

Journal of computational neuroscience
Neuronal circuits can learn and replay firing patterns evoked by sequences of sensory stimuli. After training, a brief cue can trigger a spatiotemporal pattern of neural activity similar to that evoked by a learned stimulus sequence. Network models s...

Regular graphs maximize the variability of random neural networks.

Physical review. E, Statistical, nonlinear, and soft matter physics
In this work we study the dynamics of systems composed of numerous interacting elements interconnected through a random weighted directed graph, such as models of random neural networks. We develop an original theoretical approach based on a combinat...

Classifying Stress From Heart Rate Variability Using Salivary Biomarkers as Reference.

IEEE transactions on neural networks and learning systems
An accurate and noninvasive stress assessment from human physiology is a strenuous task. In this paper, a pattern recognition system to learn complex correlates between heart rate variability (HRV) features and salivary stress biomarkers is proposed....

Robust Integral of Neural Network and Error Sign Control of MIMO Nonlinear Systems.

IEEE transactions on neural networks and learning systems
This paper presents a novel state-feedback control scheme for the tracking control of a class of multi-input multioutput continuous-time nonlinear systems with unknown dynamics and bounded disturbances. First, the control law consisting of the robust...

Prediction of facial deformation after complete denture prosthesis using BP neural network.

Computers in biology and medicine
With the accelerated aging of world population, complete denture prosthesis plays an increasingly important role in mouth rehabilitation. In addition to recovering stomatognathic system function, restoring the appearance of a third of the area under ...

Corticostriatal response selection in sentence production: Insights from neural network simulation with reservoir computing.

Brain and language
Language production requires selection of the appropriate sentence structure to accommodate the communication goal of the speaker - the transmission of a particular meaning. Here we consider event meanings, in terms of predicates and thematic roles, ...

Improvement in the Prediction of Ventilator Weaning Outcomes by an Artificial Neural Network in a Medical ICU.

Respiratory care
BACKGROUND: Twenty-five to 40% of patients pass a spontaneous breathing trial (SBT) but fail to wean from mechanical ventilation. There is no single appropriate and convenient predictor or method that can help clinicians to accurately predict weaning...

A Theory of Cheap Control in Embodied Systems.

PLoS computational biology
We present a framework for designing cheap control architectures of embodied agents. Our derivation is guided by the classical problem of universal approximation, whereby we explore the possibility of exploiting the agent's embodiment for a new and m...