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Article Citation - WoS: 13Citation - Scopus: 12Novel Global Robust Stability Criterion for Neural Networks With Delay(Pergamon-elsevier Science Ltd, 2009) Singh, Vimal; Sıngh, Vımal; Sıngh, Vımal; Department of Mechatronics Engineering; Department of Mechatronics EngineeringA novel criterion for the global robust stability of Hopfield-type interval neural networks with delay is presented. An example illustrating the improvement of the present criterion over several recently reported criteria is given. (C) 2008 Elsevier Ltd. All rights reserved.Article Citation - WoS: 30Citation - Scopus: 30New approach to stability of 2-D discrete systems with state saturation(Elsevier, 2012) Singh, VimalA new criterion for the global asymptotic stability of 2-D discrete systems described by the Roesser model using saturation arithmetic is presented. The criterion is a generalization over an earlier criterion due to Liu and Michel. The generalized criterion has the feature that Lyapunov matrix P is not restricted to be symmetric, i.e., P can be even unsymmetric. A modified form of the criterion is also presented. Two examples showing the effectiveness of the generalized approach to yield new 2-D stability results are provided. To the best of author's knowledge, the use of unsymmetric P to obtain new 2-D stability conditions (i.e., conditions which are outside the scope of symmetric P) is demonstrated, for first time, in this paper. (C) 2011 Elsevier B.V. All rights reserved.Article Citation - WoS: 14Citation - Scopus: 15Global asymptotic stability of 2-D state-space digital filters with saturation arithmetic: Modified approach(Elsevier Science Bv, 2008) Singh, VimalA criterion for the global asymptotic stability of 2-D state-space digital filters described by the Roesser model employing state saturation arithmetic is presented. The criterion is a modified form of a recently reported criterion. An example shows the effectiveness of the modified criterion. (C) 2007 Elsevier B.V. All rights reserved.Article Citation - WoS: 5Citation - Scopus: 6A new frequency-domain criterion for elimination of limit cycles in fixed-point state-space digital filters using saturation arithmetic(Pergamon-elsevier Science Ltd, 2007) Singh, VimalIn [Singh V. Elimination of overflow oscillations in fixed-point state-space digital filters using saturation arithmetic. IEEE Trans Circ Syst 1990;37(6):814-8], a frequency-domain criterion for the suppression of limit cycles in fixed-point state-space digital filters using saturation overflow arithmetic was presented. The passivity property owing to the presence of multiple saturation nonlinearities was exploited therein. In the present paper, a new notion of passivity, namely, that involving the state variables is considered, thereby arriving at an entirely new frequency-domain criterion for the suppression of limit cycles in such filters. (C) 2006 Elsevier Ltd. All rights reserved.Article Citation - WoS: 13Citation - Scopus: 14Improved Global Robust Stability for Interval-Delayed Hopfield Neural Networks(Springer, 2008) Singh, VimalA modified form of a recent criterion for the global robust stability of interval-delayed Hopfield neural networks is presented. The effectiveness of the modified criterion is demonstrated with the help of an example.Article Citation - WoS: 5Citation - Scopus: 52-D Digital Filter Realization Without Overflow Oscillations(Pergamon-elsevier Science Ltd, 2013) Singh, VimalA novel criterion for the elimination of overflow oscillations in 2-D state-space digital filters described by the Roesser model employing two's complement overflow arithmetic is presented. The criterion takes the form of linear matrix inequality (LMI) and, hence, is computationally tractable. The criterion is a generalization and improvement over an earlier criterion. An example shows the effectiveness of the new criterion. (C) 2012 Elsevier Ltd. All rights reserved.Letter Citation - WoS: 3Citation - Scopus: 3Global Robust Stability of Interval Delayed Neural Networks: Modified Approach(Wiley, 2009) Singh, VimalA criterion for the global robust stability of Hopfield-type delayed neural networks with the intervalized network parameters is presented. The criterion, which is derived by utilizing the idea of splitting the given interval into two intervals, is in the form of linear matrix inequality and, hence, computationally tractable. The criterion yields a less conservative condition compared with many recently reported criteria, as is demonstrated with an example. Copyright (C) 2008 John Wiley & Sons, Ltd.Article Citation - WoS: 1Citation - Scopus: 1Novel Frequency-Domain Criterion for Elimination of Limit Cycles in a Class of Digital Filters With Single Saturation Nonlinearity(Pergamon-elsevier Science Ltd, 2008) Singh, VimalA frequency-domain criterion for the elimination of limit cycles in a class of digital filters utilizing single saturation nonlinearity is presented. The criterion is derived by exploiting the structural properties of the system under consideration in a greater detail. A novel feature of the criterion is that it takes the form of a matrix inequality, despite the fact that there is single nonlinearity in the system. An example showing the effectiveness of the criterion is given. (c) 2006 Elsevier Ltd. All rights reserved.Article Citation - WoS: 18Citation - Scopus: 18Stability Analysis of 2-D Linear Discrete Systems Based on the Fornasini-Marchesini Second Model: Stability With Asymmetric Lyapunov Matrix(Academic Press inc Elsevier Science, 2014) Singh, VimalThe stability of two-dimensional (2-D) linear discrete systems based on the Fornasini-Marchesini local state-space (LSS) model is considered. A stability criterion using the asymmetric Lyapunov matrix P is presented. A special case of the criterion is discussed. (C) 2013 Elsevier Inc. All rights reserved.Article Citation - WoS: 7Citation - Scopus: 8Some Remarks on Global Asymptotic Stability of Neural Networks With Constant Time Delay(Pergamon-elsevier Science Ltd, 2007) Singh, VimalAn elegant proof of a previously reported criterion for the uniqueness and global asymptotic stability of the equilibrium point of a class of neural networks with constant time delay is presented. The present proof yields some interesting observations. (c) 2005 Elsevier Ltd. All rights reserved.
