A delay-dependent LMI approach to dynamics analysis of discrete-time recurrent neural networks with time-varying delays

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier Ltd.In this Letter, the analysis problem for the existence and stability of periodic solutions is investigated for a class of general discrete-time recurrent neural networks with time-varying delays. For the neural networks under study, a generalized activation function is considered, and the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By employing the latest free-weighting matrix method, an appropriate Lyapunov–Krasovskii functional is constructed and several sufficient conditions are established to ensure the existence, uniqueness, and globally exponential stability of the periodic solution for the addressed neural network. The conditions are dependent on both the lower bound and upper bound of the time-varying time delays. Furthermore, the conditions are expressed in terms of the linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Two simulation examples are given to show the effectiveness and less conservatism of the proposed criteria.This work was supported in part by the National Natural Science Foundation of China under Grant 50608072, an International Joint Project sponsored by the Royal Society of the UK and the National Natural Science Foundation of China, and the Alexander von Humboldt Foundation of Germany

On the predominant mechanisms active during the high power diode laser modification of the wettability characteristics of an SiO2/Al2O3-based ceramic material

The mechanisms responsible for modifications to the wettability characteristics of a SiO2/Al2O3-based ceramic material in terms of a test liquid set comprising of human blood, human blood plasma, glycerol and 4-octonol after high power diode laser (HPDL) treatment have been elucidated. Changes in the contact angle, , and hence the wettability characteristics of the SiO2/Al2O3-based ceramic were attributed primarily to: modifications to the surface roughness of the ceramic resulting from HPDL interaction which accordingly effected reductions in ; the increase in the surface O2 content of the ceramic after HPDL treatment; since an increase in surface O2 content intrinsically brings about a decrease in , and vice versa and the increase in the polar component of the surface energy, due to the HPDL induced surface melting and resolidification which consequently created a partially vitrified microstructure that was seen to augment the wetting action. However, the degree of influence exerted by each mechanism was found to differ markedly. Isolation of each of these mechanisms permitted the magnitude of their influence to be qualitatively determined. Surface energy, by way of microstructural changes, was found to be by far the most predominant element governing the wetting characteristics of the SiO2/Al2O3-based ceramic. To a much lesser extent, surface O2 content, by way of process gas, was also seen to influence to a changes in the wettability characteristics of the SiO2/Al2O3-based ceramic, whilst surface roughness was found to play a minor role in inducing changes in the wettability characteristics

An intelligent genetic algorithm for PAPR reduction in a multi-carrier CDMA wireless system

Abstract— A novel intelligent genetic algorithm (GA), called Minimum Distance guided GA (MDGA) is proposed for peak-average-power ratio (PAPR) reduction based on partial transmit sequence (PTS) scheme in a synchronous Multi-Carrier Code Division Multiple Access (MC-CDMA) system. In contrast to traditional GA, our MDGA starts with a balanced ratio of exploration and exploitation which is maintained throughout the process. It introduces a novel replacement strategy which increases significantly the convergence rate and reduce dramatically computational complexity as compared to the conventional GA. The simulation results demonstrate that, if compared to the PAPR reduction schemes using exhaustive search and traditional GA, our scheme achieves 99.52% and 50+% reduction in computational complexity respectively

Data quality: Some comments on the NASA software defect datasets

Background-Self-evidently empirical analyses rely upon the quality of their data. Likewise, replications rely upon accurate reporting and using the same rather than similar versions of datasets. In recent years, there has been much interest in using machine learners to classify software modules into defect-prone and not defect-prone categories. The publicly available NASA datasets have been extensively used as part of this research. Objective-This short note investigates the extent to which published analyses based on the NASA defect datasets are meaningful and comparable. Method-We analyze the five studies published in the IEEE Transactions on Software Engineering since 2007 that have utilized these datasets and compare the two versions of the datasets currently in use. Results-We find important differences between the two versions of the datasets, implausible values in one dataset and generally insufficient detail documented on dataset preprocessing. Conclusions-It is recommended that researchers 1) indicate the provenance of the datasets they use, 2) report any preprocessing in sufficient detail to enable meaningful replication, and 3) invest effort in understanding the data prior to applying machine learners

Symbol error rate analysis for M-QAM modulated physical-layer network coding with phase errors

Recent theoretical studies of physical-layer network coding (PNC) show much interest on high-level modulation, such as M-ary quadrature amplitude modulation (M-QAM), and most related works are based on the assumption of phase synchrony. The possible presence of synchronization error and channel estimation error highlight the demand of analyzing the symbol error rate (SER) performance of PNC under different phase errors. Assuming synchronization and a general constellation mapping method, which maps the superposed signal into a set of M coded symbols, in this paper, we analytically derive the SER for M-QAM modulated PNC under different phase errors. We obtain an approximation of SER for general M-QAM modulations, as well as exact SER for quadrature phase-shift keying (QPSK), i.e. 4-QAM. Afterwards, theoretical results are verified by Monte Carlo simulations. The results in this paper can be used as benchmarks for designing practical systems supporting PNC. © 2012 IEEE

Study on QoS support in 802.11e-based multi-hop vehicular wireless ad hoc networks

Multimedia communications over vehicular ad hoc networks (VANET) will play an important role in the future intelligent transport system (ITS). QoS support for VANET therefore becomes an essential problem. In this paper, we first study the QoS performance in multi-hop VANET by using the standard IEEE 802.11e EDCA MAC and our proposed triple-constraint QoS routing protocol, Delay-Reliability-Hop (DeReHQ). In particular, we evaluate the DeReHQ protocol together with EDCA in highway and urban areas. Simulation results show that end-to-end delay performance can sometimes be achieved when both 802.11e EDCA and DeReHQ extended AODV are used. However, further studies on cross-layer optimization for QoS support in multi-hop environment are required

Software Defect Association Mining and Defect Correction Effort Prediction

Much current software defect prediction work concentrates on the number of defects remaining in software system. In this paper, we present association rule mining based methods to predict defect associations and defect-correction effort. This is to help developers detect software defects and assist project managers in allocating testing resources more effectively. We applied the proposed methods to the SEL defect data consisting of more than 200 projects over more than 15 years. The results show that for the defect association prediction, the accuracy is very high and the false negative rate is very low. Likewise for the defect-correction effort prediction, the accuracy for both defect isolation effort prediction and defect correction effort prediction are also high. We compared the defect-correction effort prediction method with other types of methods: PART, C4.5, and Na¨ıve Bayes and show that accuracy has been improved by at least 23%. We also evaluated the impact of support and confidence levels on prediction accuracy, false negative rate, false positive rate, and the number of rules. We found that higher support and confidence levels may not result in higher prediction accuracy, and a sufficient number of rules is a precondition for high prediction accuracy