AIMC Topic: Feedback

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Finite-time cluster synchronization of multi-weighted fractional-order coupled neural networks with and without impulsive effects.

Neural networks : the official journal of the International Neural Network Society
In this paper, finite-time cluster synchronization (FTCS) of multi-weighted fractional-order neural networks is studied. Firstly, a FTCS criterion of the considered neural networks is obtained by designing a new delayed state feedback controller. Sec...

Neural operators for robust output regulation of hyperbolic PDEs.

Neural networks : the official journal of the International Neural Network Society
The recently introduced neural operator (NO) has been employed as a gain approximator in the backstepping stabilization control of first-order hyperbolic and parabolic partial differential equation (PDE) systems. Due to the global approximation abili...

Radiographical diagnostic competences of dental students using various feedback methods and integrating an artificial intelligence application-A randomized clinical trial.

European journal of dental education : official journal of the Association for Dental Education in Europe
INTRODUCTION: Radiographic diagnostic competences are a primary focus of dental education. This study assessed two feedback methods to enhance learning outcomes and explored the feasibility of artificial intelligence (AI) to support education.

Photonic deep residual time-delay reservoir computing.

Neural networks : the official journal of the International Neural Network Society
Time-delay reservoir computing (TDRC) represents a simplified variant of recurrent neural networks, employing a nonlinear node with a feedback mechanism to construct virtual nodes. The capabilities of TDRC can be enhanced by transitioning to a deep a...

Stability and synchronization of fractional-order reaction-diffusion inertial time-delayed neural networks with parameters perturbation.

Neural networks : the official journal of the International Neural Network Society
This study is centered around the dynamic behaviors observed in a class of fractional-order generalized reaction-diffusion inertial neural networks (FGRDINNs) with time delays. These networks are characterized by differential equations involving two ...

Dual-stage feedback network for lightweight color image compression artifact reduction.

Neural networks : the official journal of the International Neural Network Society
Lossy image coding techniques usually result in various undesirable compression artifacts. Recently, deep convolutional neural networks have seen encouraging advances in compression artifact reduction. However, most of them focus on the restoration o...

Efficient multi-stage feedback attention for diverse lesion in cancer image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In the domain of Computer-Aided Diagnosis (CAD) systems, the accurate identification of cancer lesions is paramount, given the life-threatening nature of cancer and the complexities inherent in its manifestation. This task is particularly arduous due...

Lag projective synchronization of discrete-time fractional-order quaternion-valued neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the lag projective synchronization (LPS) problem for a class of discrete-time fractional-order quaternion-valued neural networks(DTFO QVNNs) systems with time delays. Firstly, a DTFOQVNNs system with time delay is constructed. S...

Adaptive neural fault-tolerant prescribed performance control of a rehabilitation exoskeleton for lower limb passive training.

ISA transactions
This article studies the passive tracking problem of a wearable exoskeleton for lower limb rehabilitation therapy in the face of unmodeled dynamics, interactive friction, disturbance, prescribed performance constraints, and actuator faults. Adaptive ...

Closing the loop in minimally supervised human-robot interaction: formative and summative feedback.

Scientific reports
Human instructors fluidly communicate with hand gestures, head and body movements, and facial expressions, but robots rarely leverage these complementary cues. A minimally supervised social robot with such skills could help people exercise and learn ...