Stability analysis of uncertain fuzzy Hopfield neural networks with time delays

In this paper, the global stability problem of uncertain Takagi–Sugeno (T–S) fuzzy Hopfield neural networks with time delays (TSFHNNs) is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSFHNNs. Here, we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, in order to obtain generalized stability region. In fact, these techniques lead to generalized and less conservative stability condition that guarantee the wide stability region. The proposed stability conditions are demonstrated with four numerical examples. Comparison with other stability conditions in the literature shows our conditions are the more powerful ones to guarantee the widest stability region.     

AADS--an automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors

We report here a robust automated active site detection, docking, and scoring (AADS) protocol for proteins with known structures. The active site finder identifies all cavities in a protein and scores them based on the physicochemical properties of functional groups lining the cavities in the protein. The accuracy realized on 620 proteins with sizes ranging from 100 to 600 amino acids with known drug active sites is 100% when the top ten cavity points are considered. These top ten cavity points identified are then submitted for an automated docking of an input ligand/candidate molecule. The docking protocol uses an all atom energy based Monte Carlo method. Eight low energy docked structures corresponding to different locations and orientations of the candidate molecule are stored at each cavity point giving 80 docked structures overall which are then ranked using an effective free energy function and top five structures are selected. The predicted structure and energetics of the complexes agree quite well with experiment when tested on a data set of 170 protein-ligand complexes with known structures and binding affinities. The AADS methodology is implemented on an 80 processor cluster and presented as a freely accessible, easy to use tool at http://www.scfbio-iitd.res.in/dock/ActiveSite_new.jsp .     

Global Robust Passivity Analysis for Stochastic Interval Neural Networks with Interval Time-Varying Delays and Markovian Jumping Parameters

In this paper, the problem of passivity analysis is investigated for stochastic interval neural networks with interval time-varying delays and Markovian jumping parameters. By constructing a proper Lyapunov-Krasovskii functional, utilizing the free-weighting matrix method and some stochastic analysis techniques, we deduce new delay-dependent sufficient conditions, that ensure the passivity of the proposed model. These sufficient conditions are computationally efficient and they can be solved numerically by linear matrix inequality (LMI) Toolbox in Matlab. Finally, numerical examples are given to verify the effectiveness and the applicability of the proposed results.     

Global asymptotic stability of BAM fuzzy cellular neural networks with time delay in the leakage term,discrete and unbounded distributed delays

In this article, a class of bidirectional associative memory (BAM) fuzzy cellular neural networks (FCNNs) with time delay in the leakage term, discrete and unbounded distributed delays is formulated to study the global asymptotic stability. This approach is based on the Lyapunov–Krasovskii functional with free-weighting matrices. Using linear matrix inequality (LMI), a new set of stability criteria for BAM FCNNs with time delay in the leakage term, discrete and unbounded distributed delays is obtained. Also, the stability behavior of BAM FCNNs is very sensitive to the time delay in the leakage term. In the absence of a leakage term, a new stability criteria is also derived by employing a Lyapunov–Krasovskii functional and using the LMI approach. Our results establish a new set of stability criteria for BAM FCNNs with discrete and unbounded distributed delays. Numerical examples are provided to illustrate the effectiveness of the developed techniques.     

Delay-range dependent stability criteria for neural networks with Markovian jumping parameters

The paper is concerned with a stability analysis problem for neural networks with Markovian jumping parameters. The jumping parameters considered here are generated from a continuous-time discrete-state homogenous Markov process, which are governed by a Markov process with discrete and finite state space. A new type of Markovian jumping matrix P_i is introduced in this paper. The discrete delays are assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov–Krasovskii functional, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to demonstrate the lower conservatism and the effectiveness of the proposed LMI conditions.     

Cluster pre-existence probability

Pre-existence probability of the fragments for the complete binary spectrum of different systems such as ⁵⁶Ni, ¹¹⁶Ba, ²²⁶Ra and ²⁵⁶Fm are calculated, from the overlapping part of the interaction potential using the WKB approximation. The role of reduced mass as well as the classical hydrodynamical mass in the WKB method is analysed. Within WKB, even for negative Q -value systems, the pre-existence probability is calculated. The calculations reveal rich structural information. The calculated results are compared with the values of preformed cluster model of Gupta and collaborators. The mass asymmetry motion is shown here for the first time as a part of relative separation motion.     

Effect of misalignment of air-coupled probes on Ao Lamb mode propagating in a metal plate

Proper alignment of air-coupled ultrasonic transducers for generation and reception of Lamb waves is vital in order to acquire a high amplitude wave group. Any misalignment with either the transmitter or the receiver or both adversely influences the amplitude of a Lamb mode. This paper reports a systematic attempt to quantify the reduction in the amplitude of the fundamental anti-symmetric Lamb mode (A_o) in a metal plate caused by misalignments in air-coupled probes. Three different types of misalignments – linear, orientation and synchronised orientation were deliberately introduced in the transducers, and experiments were performed on a 6 mm thick aluminium plate. Amplitudes of A_o mode measured at various configurations were normalised with that of A_o mode, captured in a reference configuration. Suitable curves fitted over the experimental data points revealed that Gaussian curves represent appropriately the variations in normalised amplitudes of A_o mode. Moreover, analytical expressions were derived to predict the difference in arrival times of Lamb mode(s) due to orientation and synchronised orientation misalignments.     

Improving the signal amplitude of meandering coil EMATs by using ribbon soft magnetic flux concentrators (MFC)

This paper presents a new method of improving the ultrasonic signal amplitude from a meander line EMAT by using soft magnetic alloy ribbon (Fe₆₀Ni₁₀V₁₀B₂₀) as a magnetic flux concentrator (MFC). The flux concentrator is a thin soft amorphous magnetic material (Fe₆₀Ni₁₀V₁₀B₂₀) which is very sensitive to a small flux change. The MFC is used with the EMAT to improve the signal amplitude and it was observed that the peak signal amplitude increases by a factor of two compared to the signal without MFC. Two dimensional numerical models have been developed for the EMAT with MFC to quantify the improvement of the received signal amplitudes. Model calculations and experiments have been carried out for a wide range of ultrasonic frequencies (500 kHz-1 MHz) in different materials.