Filtreler

2012 - 20143
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Ayarlar

Bölüm: Işık University, Faculty of Engineering, Department of Electrical-Electronics Engineering × Konu: Criterion ×

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Listeleniyor 1 - 3 / 3
  • Küçük Resim
    Yayın
    An analysis of stability of a class of neutral-type neural networks with discrete time delays
    (Hindawi Publishing Corporation, 2013) Orman, Zeynep; Arik, Sabri
    The problem of existence, uniqueness, and global asymptotic stability is considered for the class of neutral-type neural network model with discrete time delays. By employing a suitable Lyapunov functional and using the homeomorphism mapping theorem, we derive some new delay-independent sufficient conditions for the existence, uniqueness, and global asymptotic stability of the equilibrium point for this class of neutral-type systems. The obtained conditions basically establish some norm and matrix inequalities involving the network parameters of the neural system. The main advantage of the proposed results is that they can be expressed in terms of network parameters only. Some comparative examples are also given to compare our results with the previous corresponding results and demonstrate the effectiveness of the results presented.
  • Küçük Resim
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    New robust stability results for bidirectional associative memory neural networks with multiple time delays
    (Elsevier Science Inc, 2012-08-01) Senan, Sibel; Arik, Sabri; Liu, Derong
    In this paper, the robust stability problem is investigated for a class of bidirectional associative memory (BAM) neural networks with multiple time delays. By employing suitable Lyapunov functionals and using the upper bound norm for the interconnection matrices of the neural network system, some novel sufficient conditions ensuring the existence, uniqueness and global robust stability of the equilibrium point are derived. The obtained results impose constraint conditions on the system parameters of neural network independent of the delay parameters. Some numerical examples and simulation results are given to demonstrate the applicability and effectiveness of our results, and to compare the results with previous robust stability results derived in the literature.
  • Küçük Resim
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    A new condition for robust stability of uncertain neural networks with time delays
    (Elsevier Science BV, 2014-03-27) Arik, Sabri
    This paper is concerned with the global asymptotic stability problem of dynamical neural networks with multiple time delays under parameter uncertainties. First carrying out an analysis of existence and uniqueness of the equilibrium point by means of the Homeomorphism theory, and then, studying the global asymptotic stability of the equilibrium point by constructing a suitable Lyapunov functional, we derive a new global robust stability criterion for the class of delayed neural networks with respect to the Lipschitz activation functions. The result obtained establishes a relationship between the neural network parameters only and it is independent of the time delay parameters. It is shown that the established stability condition generalizes some existing ones and it can be considered to an alternative result to some other corresponding results derived in previous literature. We also give some comparative numerical examples to demonstrate the validity and effectiveness of our proposed result.