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Computer Simulation

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Improved fixed-time stability analysis and applications to synchronization of discontinuous complex-valued fuzzy cellular neural networks.

Neural networks : the official journal of the International Neural Network Society
This article mainly centers on proposing new fixed-time (FXT) stability lemmas of discontinuous systems, in which novel optimization approaches are utilized and more relaxed conditions are required. The conventional discussions about Vt>1 and 0

Deep Learning-Based Techniques in Glioma Brain Tumor Segmentation Using Multi-Parametric MRI: A Review on Clinical Applications and Future Outlooks.

Journal of magnetic resonance imaging : JMRI
This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multiparametric magnetic resonance imaging (MRI) data. The study surveys advanced techniques such as multiparametric MRI for capturing the complex nature o...

Detecting differentially expressed genes from RNA-seq data using fuzzy clustering.

The international journal of biostatistics
A two-group comparison test is generally performed on RNA sequencing data to detect differentially expressed genes (DEGs). However, the accuracy of this method is low due to the small sample size. To address this, we propose a method using fuzzy clus...

Prescribed performance adaptive neural event-triggered control for switched nonlinear cyber-physical systems under deception attacks.

Neural networks : the official journal of the International Neural Network Society
In this paper, the design of an adaptive neural event-triggered control scheme for a class of switched nonlinear systems affected by external disturbances and deception attacks is presented. In order to address the effects caused by unknown disturban...

A Hyper-Transformer model for Controllable Pareto Front Learning with Split Feasibility Constraints.

Neural networks : the official journal of the International Neural Network Society
Controllable Pareto front learning (CPFL) approximates the Pareto optimal solution set and then locates a non-dominated point with respect to a given reference vector. However, decision-maker objectives were limited to a constraint region in practice...

Optimal synchronization with L-gain performance: An adaptive dynamic programming approach.

Neural networks : the official journal of the International Neural Network Society
This paper studies an optimal synchronous control protocol design for nonlinear multi-agent systems under partially known dynamics and uncertain external disturbance. Under some mild assumptions, Hamilton-Jacobi-Isaacs equation is derived by the perf...

Advancements in nanobody generation: Integrating conventional, in silico, and machine learning approaches.

Biotechnology and bioengineering
Nanobodies, derived from camelids and sharks, offer compact, single-variable heavy-chain antibodies with diverse biomedical potential. This review explores their generation methods, including display techniques on phages, yeast, or bacteria, and comp...

Development and Validation of an Explainable Machine Learning Model for Identification of Hyper-Functioning Parathyroid Glands from High-Frequency Ultrasonographic Images.

Ultrasound in medicine & biology
OBJECTIVE: To develop and validate a machine learning (ML) model based on high-frequency ultrasound (HFUS) images with the aim to identify the functional status of parathyroid glands (PTGs) in secondary hyper-parathyroidism (SHPT) patients.

Accelerating multipool CEST MRI of Parkinson's disease using deep learning-based Z-spectral compressed sensing.

Magnetic resonance in medicine
PURPOSE: To develop a deep learning-based approach to reduce the scan time of multipool CEST MRI for Parkinson's disease (PD) while maintaining sufficient prediction accuracy.

Input-to-state stability of delayed memristor-based inertial neural networks via non-reduced order method.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the input-to-state stability (ISS) for a kind of delayed memristor-based inertial neural networks (DMINNs). Based on the nonsmooth analysis and stability theory, novel delay-dependent and delay-independent criteria on the...