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This paper concerns with exponential convergence for a class of high-order recurrent neural networks with continuously distributed delays in the leakage terms. Without assuming the boundedness on the activation functions, some sufficient conditions are derived to ensure that all solutions of the networks converge exponentially to the zero point by using(More)
During the Hilbert-Huang transformation (HHT), time-series data are firstly decomposed into several components with different time scale (i.e. intrinsic mode function, IMF), using the empirical mode decomposition (EMD). Then, the Hilbert transformation is applied to every IMF. As a result, the HHT spectrum of the data is constructed. In this paper, the(More)
  • Weidong Jiao
  • 2008
Based on the Hilbert-Huang transform (HHT), a method for time-frequency feature extraction from vibration signals was introduced into fault diagnosis of rotors. Firstly, the empirical mode decomposition (EMD) was implemented on vibration signals measured by sensors. As a result, a set of components with different time scales, i.e. intrinsic mode function(More)
Considering time delays factors and random factors, the stability and control strategy for a class of stochastic vehicle following systems with delays are studied. By applying vector Lyapunov function method, sufficient conditions for exponential stability of the system are obtained. Based on the random vehicles longitudinal dynamics model, which is(More)
In order to research characteristics of unbalanced rotor system with external excitations, a dynamic model of rotor was established. This model not only considered the influences of the gyroscopic effect and the gravity, but also includes two kinds of unbalance which named static/dynamic unbalance. Use the hypothesis of small angle, expression of forces and(More)
Independent Component Analysis (ICA) is a powerful tool for redundancy reduction and nongaussian data analysis. And, Artificial Neural Network (ANN), especially the Self-Organizing Map (SOM) based on unsupervised learning is a kind of excellent method for pattern clustering and recognition. By combining ICA with ANN, we proposed a novel compound neural(More)
Unbalance, fatigue crack and rotor-stator rub are the three common and important faults in a rotor-bearing system. They are originally interconnected each other, and their vibration behaviors do often show strong nonlinear and transient characteristic, especially when more than one of them coexist in the system. This article is aimed to study the vibration(More)
A method is proposed for fault diagnosis of rotor systems, with independent component analysis (ICA) based feature extraction and multi-layer perceptron (MLP) based pattern classification. By the use of ICA, feature vectors are integratedly extracted from multichannel vibration measurements collected under different operating patterns (in term of rotating(More)
A novel classifier is proposed for fault diagnosis of rotor system, with independent component analysis (ICA) based feature extraction and multi-layer perceptron (MLP) based pattern classification. By the use of ICA, feature vectors are integratedly extracted from multi-channel vibration measurements collected under different operating patterns (in term of(More)