Event-Triggered Output-Feedback Control for Synchronization of Delayed Neural Networks.

This article proposes a novel discrete event-triggered scheme (DETS) for the synchronization of delayed neural networks (NNs) using the dynamic output-feedback controller (DOFC). The proposed DETS uses both the current and past samples to determine the next trigger, unlike the traditional event-triggered scheme (ETS) that uses only the current sample. The proposed DETS is employed in a dual setup for two network channels to significantly reduce redundant data transmission.

A sum-based discrete event-triggered dynamic output feedback control for interval type-2 fuzzy systems.

The current study concentrates on the event-based controller design for nonlinear networked systems characterized by the interval type-2 (IT2) fuzzy model. An innovative sum-based discrete event-triggered mechanism (SDETM), whose triggering condition includes several previous measurement samples, is proposed. Compared to the traditional event-triggered mechanism (ETM), the novel SDETM requires less network resources consumption.

An efficient framework for automated screening of Clinically Significant Macular Edema.

The present study proposes a new approach to automated screening of Clinically Significant Macular Edema (CSME) and addresses two major challenges associated with such screenings, i.e., exudate segmentation and imbalanced datasets.

Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images.

Background: Anterior talofibular ligament (ATFL) is considered as the weakest ankle ligament that is most prone to injuries. Ultrasound imaging with its portable, non-invasive and non-ionizing radiation nature is increasingly being used for ATFL diagnosis. However, diagnosis of ATFL injuries requires its segmentation from ultrasound images that is a challenging task due to the existence of homogeneous intensity regions, homogeneous textures and low contrast regions in ultrasound images.