Ovidiu Bagdasar

TL;DR: Anomaly detection is concerned with identifying data patterns that deviate remarkably from the expected behavior as mentioned in this paper, which poses hard challenges in terms of information fusion, data volumes, data speed, and network/energy efficiency, to mention but the most pressing ones.

TL;DR: This paper investigates the global existence of Filippov solutions and the robust generalized Mittag-Leffler synchronization of fractional order neural networks with discontinuous activation and impulses and demonstrates the effectiveness of four numerical simulations.

TL;DR: In this article, the authors jointly supported with the financial support of RUSA - Phase 2.0 grant sanctioned vide letter No. F.24-51/2014-U (TNMulti-Gen), Dept.of Education Govt. of India, Thailand research grant fund (RSA5980019), the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence under Grant No. BM2017002.

TL;DR: Under the framework of Filippov theory and differential inclusion theoretical analysis, some global asymptotic stability conditions for FCGNNDDs is derived by limiting discontinuous neuron activation functions by means of the given growth condition.

TL;DR: In this article, the structure and organization of Sicilian Mafia gangs were revealed based on two real-world datasets, and insights as to how to efficiently reduce the Largest Connected Component (LCC) of two networks derived from them.