AIMC Topic: Time Factors

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Observer-based state estimation for discrete-time semi-Markovian jump neural networks with round-robin protocol against cyber attacks.

Neural networks : the official journal of the International Neural Network Society
This paper investigates an observer-based state estimation issue for discrete-time semi-Markovian jump neural networks with Round-Robin protocol and cyber attacks. In order to avoid the network congestion and save the communication resources, the Rou...

Novel LKF Method on H Synchronization of Switched Time-Delay Systems.

IEEE transactions on cybernetics
This article investigates H global asymptotic synchronization (GAS) of switched nonlinear systems with delay. By introducing mode-dependent double event-triggering mechanisms (DETMs), the communication resources in both system-controller (S-C) channe...

Anti-Synchronization of Discrete-Time Fuzzy Memristive Neural Networks via Impulse Sampled-Data Communication.

IEEE transactions on cybernetics
This work is concerned with the anti-synchronization (A-S) of drive-response (D-R) memristive neural networks (MNNs) based on fuzzy rules. A novel impulsive sampled-data communication mechanism is proposed by considering information security of the M...

Training Novel Adaptive Fuzzy Cognitive Map by Knowledge-Guidance Learning Mechanism for Large-Scale Time-Series Forecasting.

IEEE transactions on cybernetics
A fuzzy cognitive map (FCM) is a graph-based knowledge representation model wherein the connections of the nodes (edges) represent casual relationships between the knowledge items associated with the nodes. This model has been applied to solve variou...

Reduction of SPECT acquisition time using deep learning: A phantom study.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Single photon emission computed tomography (SPECT) procedures are characterized by long acquisition time to acquire diagnostically acceptable image data. The goal of this investigation was to assess the feasibility of using a deep convolutional neura...

Using deep learning-derived image features in radiologic time series to make personalised predictions: proof of concept in colonic transit data.

European radiology
OBJECTIVES: Siamese neural networks (SNN) were used to classify the presence of radiopaque beads as part of a colonic transit time study (CTS). The SNN output was then used as a feature in a time series model to predict progression through a CTS.

Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

Journal of medical Internet research
BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people's expressions on social...

Fixed-time synchronization for quaternion-valued memristor-based neural networks with mixed delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, the fixed-time synchronization (FXTSYN) of unilateral coefficients quaternion-valued memristor-based neural networks (UCQVMNNs) with mixed delays is investigated. A direct analytical approach is suggested to obtain FXTSYN of UCQVMNNs u...

Using artificial neural networks to accelerate flowsheet optimization for downstream process development.

Biotechnology and bioengineering
An optimal purification process for biopharmaceutical products is important to meet strict safety regulations, and for economic benefits. To find the global optimum, it is desirable to screen the overall design space. Advanced model-based approaches ...

Reachable set estimation and stochastic sampled-data exponential synchronization of Markovian jump neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, the stochastic sampled-data exponential synchronization problem for Markovian jump neural networks (MJNNs) with time-varying delays and the reachable set estimation (RSE) problem for MJNNs subjected to external disturbances are investi...