Modal identification based on Hilbert-Huang Transform of structural response with S VD preprocessing

In recent years, Empirical mode decomposition and Hilbert spectral analysis have been combined to identify system parameters. Singular-Value Decomposition is pro- posed as a signal preprocessing technique of Hilbert-Huang Transform to extract modal parameters for closely spaced modes and low-energy components. The proposed method is applied to a simulated airplane model built in Automatic Dynamic Analysis of Mechanical Systems software. The results demonstrate that the identified modal parameters are in good agreement with the baseline model.

LARGE TIME BEHAVIOR OF SOLUTIONS TO THE PERTURBED HASEGAWA-MIMA EQUATION

The large time behavior of solutions to the two-dimensional perturbed Hasegawa- Mima equation with large initial data is studied in this paper. Based on the time-frequency decomposition and the method of Green function, we not only obtain the optimal decay rate but also establish the pointwise estimate of global classical solutions.

Convex Variational Formulation with Smooth Coupling for Multicomponent Signal Decomposition and Recovery

A convex variational formulation is proposed to solve multicomponent signal processing problems in Hilbert spaces.The cost function consists of a separable term, in which each component is modeled through its own potential,and of a coupling term, in which constraints on linear transformations of the components are penalized with smooth functionals.An algorithm with guaranteed weak convergence to a solution to the problem is provided.Various multicomponent signal decomposition and recovery applications are discussed.

Matrices Associated with Moving Least-Squares Approximation and Corresponding Inequalities

In this article, some properties of matrices of moving least-squares approximation have been proven. The used technique is based on known inequalities for singular-values of matrices. Some inequalities for the norm of coefficients-vector of the linear approximation have been proven.

Flame features and oscillation characteristics in near-blowout swirl-stabilized flames using high-speed OH-PLIF and mode decomposition methods

Flame features and dynamics are important to the explanation and prediction of a lean blowout(LBO)phenomenon.In this paper,recognition of near-LBO flame features and oscillation characterization methods were proposed based on flame spectroscopic images.High-speed planar laser-induced fluorescence measurements of OH were used to capture unique dynamic features such as the local extinction and reignition feature and entrained reactant pockets.The Zernike moment demonstrated a good performance in recognition of stability and near-LBO conditions,though the geometric moment had more advantages to characterize frequency characteristics.Low-frequency oscillations,especially at the obvious self-excited oscillation frequency around 200 Hz,were found when approaching an LBO condition,which can be expected to be used as a novel prediction characteristic parameter of the flameout limit.Proper orthogonal decomposition(POD)and dynamic mode decomposition(DMD)were used to conduct dynamic analysis of near-LBO flames.POD modes spectra showed the unique frequency characteristics of stable and near-LBO flames,which were basically in line with those at the heat-release frequency.The primary POD modes demonstrated that the radial vibration mode dominated in a stable flame,while the rotation mode was found to exist in a near-LBO flame.Analysis of modal decomposition showed that flame shedding and agminated entrained reactant pockets were responsible for generating self-excited flame oscillations.

Combustion instability of pilot flame in a pilot bluff body stabilized combustor

Combustion instability of pilot flame has been investigated in a model pilot bluff body stabilized combustor by running the pilot flame only. The primary objectives are to investigate the pilot flame dynamics and to provide bases for the study of the interaction mechanisms between the pilot flame and the main flame. Dynamic pressures are measured by dynamic pressure transduc- ers. A high speed camera with CH＊ bandpass filter is used to capture the pilot flame dynamics. The proper orthogonal decomposition （POD） is used to further analyze the high speed images. With the increase of the pilot fuel mass flow rate, the pilot flame changes from stable to unstable state grad- ually. The combustion instability frequency is 136 Hz when the pilot flame is unstable. Numerical simulation results show that the equivalence ratios in both the shear layer and the recirculation zone increase as the pilot fuel mass flow rate increases. The mechanism of the instability of the pilot flame can be attributed to the coupling between the second order acoustic mode and the unsteady heat release due to symmetric vortex shedding. These results illustrate that the pilot fuel mass flow rate has significant influences on the dynamic stability of the pilot flame.

A general communication performance evaluation model based on routing path decomposition

The network-on-chip (NoC) architecture is a main factor affecting the system performance of complicated multi-processor systems-on-chips (MPSoCs).To evaluate the effects of the NoC architectures on communication efficiency,several kinds of techniques have been developed,including various simulators and analytical models.The simulators are accurate but time consuming,especially in large space explorations of diverse network configurations;in contrast,the analytical models are fast and flexible,providing alternative methods for performance evaluation.In this paper,we propose a general analytical model to esti-mate the communication performance for arbitrary NoCs with wormhole routing and virtual channel flow control.To resolve the inherent dependency of successive links occupied by one packet in wormhole routing,we propose the routing path decomposition approach to generating a series of ordered link categories.Then we use the traditional queuing system to derive the fine-grained transmission latency for each network component.According to our experiments,the proposed analytical model provides a good approximation of the average packet latency to the simulation results,and estimates the network throughput precisely under various NoC configurations and workloads.Also,the analytical model runs about 10 5 times faster than the cycle-accurate NoC simulator.Practical applications of the model including bottleneck detection and virtual channel allocation are also presented.

Robust low-rank data matrix approximations

We review some recent approaches to robust approximations of low-rank data matrices.We consider the problem of estimating a low-rank mean matrix when the data matrix is subject to measurement errors as well as gross outliers in some of its entries.The purpose of the paper is to make various algorithms accessible with an understanding of their abilities and limitations to perform robust low-rank matrix approximations in both low and high dimensional problems.

Design of a Discrete-time Output-feedback Based Repetitive-control System

This paper deals with the problem of designing a robust discrete output-feedback based repetitive-control system for a class of linear plants with periodic uncertainties. The periodicity of the repetitive-control system is exploited to establish a two-dimensional （2D） model that converts the design problem into a robust stabilization problem for a discrete 2D system. By employing Lyapunov stability theory and the singular-value decomposition of the output matrix, a linear-matrix-inequality （LMI） based stability condition is derived. The condition can be used directly to design the gains of the repetitive controller. Two tuning parameters in the LMI enable the preferential adjustment of control and learning. A numerical example illustrates the design procedure and demonstrates the validity of the method.

Piecewise Smooth Dynamical Systems Modeling Based on Putzer and Fibonacci-Horner Theorems:DC-DC Converters Case

The paper deals with the problem of switched dynamical systems modeling especially in DC-DC converters case study consideration. It presents two approaches to describe accurately the behavior of this class of systems. To clarify the paper＇s contribution, the proposed approaches are validated through simulations and experimental results. A comparative study, between the obtained results and those of other techniques from the literature, is given to evaluate the performances of the studied approaches.

A multirate DSP structure for the identification of protein-coding regions

The identification of protein-coding regions in DNA sequence using digital signal process- ing methods is one of the central issues in bioinformatics. In this paper, a multirate struc- ture is proposed for the identification of protein-coding regions whose input sampling rate is same as output sampling rate. The multirate structure consists of cascade com- bination of decimation filter, kernel filter and interpolation filter. The decimation filter is a complex filter, the kernel filter is an FIR lowpass filter and the interpolation filter is a moving average filter. Polyphase decomposition is applied on both decimation filter and interpolation filter for computationally efficient implementation. The potential of the proposed method is evaluated in comparison with existing methods using standard datasets. The results show that the proposed method improves the identification accu- racy of protein-coding regions to a great extent compared to its counterparts.