arXiv subjects

Masoud Shafiee

Publications and source records attributed to Masoud Shafiee.

3 recordsLinked to original sources

arXiv2023

Improved Stability and Controller Design Criteria for Two-dimensional Differential-Algebraic-Equation Systems via LMI Approach

This paper addresses issues concerning asymptotic stability testing and controller design for the two-dimensional Rosser model in Differential-Algebraic-Equations systems (DAEs). We present sufficient stability criteria based on the Lyapunov approach, utilizing a set of Linear-Matrix-Inequalities (LMIs) tailored for two-dimensional DAEs. Furthermore, we establish a set of sufficient conditions for determining the feasibility of both state- and output-feedback controllers. Our methods eliminate the need for decomposing the two-dimensional DAEs into separate algebraic and differential components.

eess.SY↗

arXiv2017

An adaptive thresholding approach for automatic optic disk segmentation

Optic disk segmentation is a prerequisite step in automatic retinal screening systems. In this paper, we propose an algorithm for optic disk segmentation based on a local adaptive thresholding method. Location of the optic disk is validated by intensity and average vessel width of retinal images. Then an adaptive thresholding is applied on the temporal and nasal part of the optic disc separately. Adaptive thresholding, makes our algorithm robust to illumination variations and various image acquisition conditions. Moreover, experimental results on the DRIVE and KHATAM databases show promising results compared to the recent literature. In the DRIVE database, the optic disk in all images is correctly located and the mean overlap reached to 43.21%. The optic disk is correctly detected in 98% of the images with the mean overlap of 36.32% in the KHATAM database.

cs.CV↗

arXiv2012

Hybrid systems modeling for gas transmission network

Gas Transmission Networks are large-scale complex systems, and corresponding design and control problems are challenging. In this paper, we consider the problem of control and management of these systems in crisis situations. We present these networks by a hybrid systems framework that provides required analysis models. Further, we discuss decision-making using computational discrete and hybrid optimization methods. In particular, several reinforcement learning methods are employed to explore decision space and achieve the best policy in a specific crisis situation. Simulations are presented to illustrate the efficiency of the method.

cs.AI↗