A Review of Internet Addiction on the Basis of Different Countries (2007–2017)

This chapter presents a review of Internet addiction on the basis of different countries between the years of 2007 and 2017. For this purpose, the term “addiction” is explained, some addiction types are examined, the differences between Internet addiction and the other ones are given and the Internet addiction status of different countries are presented. In today's world, Internet addiction is a privileged problem in almost all of the countries but especially a few countries have important number of studies about the subject. The most studies are completed in China, Turkey, Taiwan, Hong Kong and Korea. In this chapter, studies about these countries and some other ones are investigated. These studies show that the “Far East” is suffering from the problem a bit more than the others. </jats:p

Global convergence analysis of delayed bidirectional associative memory neural networks

This paper studies the stability properties of a more general class of bidirectional associative memory (BAM) neural networks with constant time delays. Without assuming the symmetry of the interconnection matrices, and monotonicity and differentiability of the activation functions, we derive a new sufficient condition for the global asymptotic stability of the equilibrium point for bidirectional associative memory neural networks. The obtained results are independently of the delay parameters and can be easily verified. The results are also compared with the previous results derived in the literature

Global robust stability analysis of uncertain neural networks with time varying delays

This paper deals with the global robust stability analysis of dynamical neural networks with time varying delays. By combining Lyapunov stability theorems and Homeomorphic mapping theorem, we obtain some original sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point with respect to Lipschitz activation functions and under parameter uncertainties of the neural system. We also prove that the obtained robust stability conditions generalize some of the previously published corresponding literature results. The conditions we present can be easily verified as the conditions that are expressed in terms of the network parameters. Some comparative numerical examples are presented to demonstrate the advantages of our conditions over the previously published robust stability results. (C) 2015 Elsevier B.V. All rights reserved

New results for global stability of a class of neutral-type neural systems with time delays

This paper studies the global convergence properties of a class of neutral-type neural networks with discrete time delays. This class of neutral systems includes Cohen-Grossberg neural networks, Hopfield neural networks and cellular neural networks. Based on the Lyapunov stability theorems, some delay independent sufficient conditions for the global asymptotic stability of the equilibrium point for this class of neutral-type systems are derived. It is shown that the results presented in this paper for neutral-type delayed neural networks are the generalization of a recently reported stability result. A numerical example is also given to demonstrate the applicability of our proposed stability criteria. (C) 2009 Elsevier Inc. All rights reserved

Flood algorithm: a novel metaheuristic algorithm for optimization problems

Metaheuristic algorithms are an important area of research that provides significant advances in solving complex optimization problems within acceptable time periods. Since the performances of these algorithms vary for different types of problems, many studies have been and need to be done to propose different metaheuristic algorithms. In this article, a new metaheuristic algorithm called flood algorithm (FA) is proposed for optimization problems. It is inspired by the flow of flood water on the earth’s surface. The proposed algorithm is tested both on benchmark functions and on a real-world problem of preparing an exam seating plan, and the results are compared with different metaheuristic algorithms. The comparison results show that the proposed algorithm has competitive performance with other metaheuristic algorithms used in the comparison in terms of solution accuracy and time