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Communication

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Resilient Asynchronous State Estimation for Markovian Jump Neural Networks Subject to Stochastic Nonlinearities and Sensor Saturations.

IEEE transactions on cybernetics
This article studies the problem of dissipativity-based asynchronous state estimation for a class of discrete-time Markov jump neural networks subject to randomly occurring nonlinearities, sensor saturations, and stochastic parameter uncertainties. F...

Analysis on the Reform and Development of Physical Education Services in the Context of 5G Connected Communication.

Computational intelligence and neuroscience
With the continuous growth of science and technology, mankind has entered the fifth-generation (5G) era. In this background, the development of many fields will face great opportunities and challenges, including the field of physical education (PE). ...

Trends and frontiers of atmospheric duct research based on CiteSpace and deep learning.

Environmental science and pollution research international
The research of evaporation duct is of fundamental importance in the radar and signal communication industry. Particularly, in a real atmosphere environment, most of the radar holes cannot be corrected in time because of the persistent evaporation du...

A Novel Deep Framework for English Communication Based on Educational Psychology Perspective.

Frontiers in public health
The impact of verbal reading practices on learning is examined from the perspective of educational psychology, using the motivation theory and the schema theory. This research intends to enhance learner's English communication abilities in response t...

Study on the Application of Visual Communication Design in APP Interface Design in the Context of Deep Learning.

Computational intelligence and neuroscience
Visual communication concepts enable linguistics or semiotics to the teaching of visual communication designs, creating graphic designs into an innovative and scientific discipline. The use of storyline techniques in visual communication not only ins...

Approximation in shift-invariant spaces with deep ReLU neural networks.

Neural networks : the official journal of the International Neural Network Society
We study the expressive power of deep ReLU neural networks for approximating functions in dilated shift-invariant spaces, which are widely used in signal processing, image processing, communications and so on. Approximation error bounds are estimated...

Contemporary Value Assessment of Marxist Ideology under the Context of Deep Learning.

Computational and mathematical methods in medicine
As a conceptual superstructure, ideology plays a very important role in national security, social stability, and healthy economic development. As a result, ideological work is critical to the Party's success, and the current focus of ideological work...

A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks.

Sensors (Basel, Switzerland)
Wireless Underground Sensor Networks (WUSNs) have been showing prospective supervising application domains in the underground region of the earth through sensing, computation, and communication. This paper presents a novel Deep Learning (DL)-based Co...

The use of artificial intelligence and virtual reality in doctor-patient risk communication: A scoping review.

Patient education and counseling
OBJECTIVES: While the development of artificial intelligence (AI) and virtual reality (VR) technologies in medicine has been significant, their application to doctor-patient communication is limited. As communicating risk is a challenging, yet essent...

Usage of Evolutionary Algorithms in Swarm Robotics and Design Problems.

Sensors (Basel, Switzerland)
In this study, the general structure of swarm robotics is examined. Algorithms inspired by nature, which form the basis of swarm robotics, are introduced. Communication topologies in robotic swarms, which are similar to the communication methods betw...