AIMC Topic: Feedback

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Adaptive discrete-time neural prescribed performance control: A safe control approach.

Neural networks : the official journal of the International Neural Network Society
Most existing results on prescribed performance control (PPC), subject to input saturation and initial condition limitations, focus on continuous-time nonlinear systems. This article, as regards discrete-time nonlinear systems, is dedicated to constr...

Output sampling synchronization and state estimation in flux-charge domain memristive neural networks with leakage and time-varying delays.

Neural networks : the official journal of the International Neural Network Society
This paper theoretically explores the coexistence of synchronization and state estimation analysis through output sampling measures for a class of memristive neural networks operating within the flux-charge domain. These networks are subject to const...

Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology.

Scientific reports
Human visual attention allows prior knowledge or expectations to influence visual processing, allocating limited computational resources to only that part of the image that are likely to behaviourally important. Here, we present an image recognition ...

Delayed-feedback oscillators replicate the dynamics of multiplex networks: Wavefront propagation and stochastic resonance.

Neural networks : the official journal of the International Neural Network Society
The widespread development and use of neural networks have significantly enriched a wide range of computer algorithms and promise higher speed at lower cost. However, the imitation of neural networks by means of modern computing substrates is highly ...

Optimization control for mean square synchronization of stochastic semi-Markov jump neural networks with non-fragile hidden information and actuator saturation.

Neural networks : the official journal of the International Neural Network Society
This paper studies the asynchronous output feedback control and H synchronization problems for a class of continuous-time stochastic hidden semi-Markov jump neural networks (SMJNNs) affected by actuator saturation. Initially, a novel neural networks ...

Enhancing the performance of a resonance-based sensor network for soft robots using binary excitation.

Bioinspiration & biomimetics
Embedded, flexible, multi-sensor sensing networks have shown the potential to provide soft robots with reliable feedback while navigating unstructured environments. Time delay associated with extracting information from these sensing networks and the...

A bio-inspired visual collision detection network integrated with dynamic temporal variance feedback regulated by scalable functional countering jitter streaming.

Neural networks : the official journal of the International Neural Network Society
In pursuing artificial intelligence for efficient collision avoidance in robots, researchers draw inspiration from the locust's visual looming-sensitive neural circuit to establish an efficient neural network for collision detection. However, existin...

Barrier-critic-disturbance approximate optimal control of nonzero-sum differential games for modular robot manipulators.

Neural networks : the official journal of the International Neural Network Society
In this paper, for addressing the safe control problem of modular robot manipulators (MRMs) system with uncertain disturbances, an approximate optimal control scheme of nonzero-sum (NZS) differential games is proposed based on the control barrier fun...

Tracking control problem of nonlinear strict-feedback systems with input nonlinearity: An adaptive neural network dynamic surface control method.

PloS one
In this work, the tracking control problem for a class of nonlinear strict-feedback systems with input nonlinearity is addressed. In response to the influence of input nonlinearity, an auxiliary control system is constructed to compensate for it. To ...

FusionOC: Research on optimal control method for infrared and visible light image fusion.

Neural networks : the official journal of the International Neural Network Society
Infrared and visible light image fusion can solve the limitations of single-type visual sensors and can boost the target detection performance. However, since the traditional fusion strategy lacks the controllability and feedback mechanism, the fusio...