Globally exponentially attractive sets of the family of Lorenz systems

In this paper, the concept of globally exponentially attractive set is proposed and used to consider the ultimate bounds of the family of Lorenz systems with varying parameters. Explicit estimations of the ultimate bounds are derived. The results presented in this paper contain all the existing results as special cases. In particular, the critical cases, b→ 1^＋ and a→0^＋, for which the previous methods failed, have been solved using a unified formula.     

A Trust-Based Approach to Estimating the Confidence of the Software System in Open Environments

Emerging with open environments, the software paradigms, such as open resource coalition and Internetware, present several novel characteristics including user-centric, non-central control, and continual evolution. The goal of obtaining high confidence on such systems is more di?cult to achieve. The general developer-oriented metrics and testing-based methods which are adopted in the traditional measurement for high confidence software seem to be infeasible in the new situation. Firstly, the software develo...     

Minimum-energy wavelet frame on the interval

The construction and properties of interval minimum-energy wavelet frame are systematically studied in this paper. They are as follows： 1） give the definition of interval minimum-energy wavelet frame; 2） give the necessary and sufficient conditions for the minimum-energy frames for L^2[0,1]; 3） present the construction algorithm for minimum-energy wavelet frame associated with refinable functions on the interval with any support y; 4） give the decomposition and reconstruction formulas of the minimum-energy frame on the interval [0,1],     

Power allocation for non-orthogonal decode-and-forward cooperation protocol

This paper studies the power allocation problem for the non-orthogonal decode-and-forward (NDF) cooperation protocol with selection relaying. With the availability of the magnitudes of all channel gains at the source, the power allocation is explored that maximizes the mutual information between the source and destination subject to a total power constraint. The minimum power that avoids the outage of the relay is set as a condition, under which the power allocation problem becomes one of selecting the optimal one from several allocation factor triplets. It is shown that the power allocation scheme can provide considerable performance gain, and the non-orthogonal cooperation protocol is superior to the orthogonal protocol and direct transmission. Supported by the Project of Natural Science Foundation of Jiangsu Province (Grant No. BK2006701), the National Natural Science Foundation of China (Grant No. 60672079), and the National High-Tech Research & Development Program of China (Grant No. 2007AA01Z267)     

Clustered Chain Path Index for XML Document: Efficiently Processing Branch Queries

Branch query processing is a core operation of XML query processing. In recent years, a number of stack based twig join algorithms have been proposed to process twig queries based on tag stream index. However, in tag stream index, each element is labeled separately without considering the similarity among elements. Besides, algorithms based on tag stream index perform inefficiently on large document. This paper proposes a novel index, named Clustered Chain Path Index, based on a novel labeling scheme. This index provides efficient support for processing branch queries. It also has the same cardinality as 1-index against tree structured XML document. Based on CCPI, efficient algorithms, KMP-Match-Path and Related-Path-Segment-Join, are proposed to process queries efficiently. Analysis and experimental results show that proposed query processing algorithms based on CCPI outperform other algorithms and have good scalability. This paper is partially supported by Natural Science Foundation of Heilongjiang Province, Grant No. zjg03-05 and National Natural Science Foundation of China, Grant No. 60473075 and Key Program of the National Natural Science Foundation of China, Grant No. 60533110.     

Neural Network Algorithm for Designing FIR Filters Utilizing Frequency-Response Masking Technique

This paper presents a new joint optimization method for the design of sharp linear-phase finite-impulse response (FIR) digital filters which are synthesized by using basic and multistage frequency-response-masking(FRM) techniques.The method is based on a batch back-propagation neural network algorithm with a variable learning rate mode.We propose the following two-step optimization technique in order to reduce the complexity.At the first step,an initial FRM filter is designed by alternately optimizing th...     

Multi-spectral image fusion method based on two channels non-separable wavelets

A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1,-1] and its application in the fusion of multi-spectral image are presented. Many 4×4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform.     

An improved description method of the bumpy texture

Bump mapping is a texture-based rendering approach for simulating surface details to make its illumination results have three-dimensional effects. The bumpy properties of an object are determined by height maps. But in the process of generating height maps, a problem arises, i.e. to get a correct value of the pixel height, empirical data should be calculated repeatedly, which proves very complicated, and meanwhile the realistic rendering effect is reduced, because the bumpy property is exaggerated in the height map. Therefore, in this paper, we present a method for describing the details of the bumpy texture, where a new concept “bumpy map” is introduced to replace the height map. Experimental results demonstrate that the bumpy details produced by the “bumpy map” are more consistent with the original bumpy texture than by the method of height map. Supported partially by the National Natural Science Foundation of China (Grant Nos. 60533030, 60825203, 60572104), National High-Tech Research & Development Program of China (Grant No.2006AA01Z317), Science and Technology Development Program of Education Commission in Beijing (Grant No. KM200710005017)     

Receding horizon estimation to networked control systems with multirate scheme

This paper investigates the problem of receding horizon state estimation for networked control systems (NCSs) with random network-induced delays less than one sample period, which are formulated as multirate control systems. Based on a batch of recent past slow rate measurements in a finite horizon window, the initial state estimation in this window is solved by minimizing a receding-horizon objective function, and then the fast rate state estimations are calculated by the prediction of dynamic equation to compensate for the network-induced time delays. Furthermore, convergence results and unbiasedness properties are analyzed. An upper bound of estimation error is presented under the assumption of bounded disturbances acting on the system and measurement equations. A simulation example shows the effectiveness of the proposed method. Supported by the National Natural Science Foundation of China (Grant Nos. 60774015, 60674018, 60825302), the National High-Tech Research & Development Program of China (Grant No. 2006AA04Z173), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20060248001), and partly by Shanghai Natural Science Foundation (Grant No. 07JC14016)     

Demand-Driven Memory Leak Detection Based on Flow- and Context-Sensitive Pointer Analysis

We present a demand-driven approach to memory leak detection algorithm based on flow- and context-sensitive pointer analysis. The detection algorithm firstly assumes the presence of a memory leak at some program point and then runs a backward analysis to see if this assumption can be disproved. Our algorithm computes the memory abstraction of programs based on points-to graph resulting from flow- and context-sensitive pointer analysis. We have implemented the algorithm in the SUIF2 compiler infrastructure and used the implementation to analyze a set of C benchmark programs. The experimental results show that the approach has better precision with satisfied scalability as expected. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60725206, 60673118, and 90612009, the National High-Tech Research and Development 863 Program of China under Grant No. 2006AA01Z429, the National Basic Research 973 Program of China under Grant No. 2005CB321802, the Program for New Century Excellent Talents in University under Grant No. NCET-04-0996, and the Hunan Natural Science Foundation under Grant No. 07JJ1011.     

SNR estimation algorithm based on the preamble for wireless OFDM systems

Based on the analysis of the performance of Boumard＇s SNR method for wireless orthogonal frequency division multiplexing （OFDM） systems, a new estimation algorithm of the noise variance is proposed by only using the data samples of the two training symbols in the preamble, and the second order moment of these data samples is employed to estimate the signal power. The average SNR and the SNRs on the subchannels can all be estimated by the proposed algorithm, and its performance is independent of the channel＇s frequency selectivity. Simulation results show that the performance of the proposed method is highly improved and much better than that of Boumard＇s method.     

W^1,2（Ω）- and X^1,2（Ω）-stability of reaction- diffusion cellular neural networks with delay

With Poincare＇s inequality and auxiliary function applied in a class of retarded cellular neural networks with reaction-diffusion, the conditions of the systems＇ W^1,2（Ω）-exponential and X^1,2（Ω）-asmptotic stability are obtained. The stability conditions containing diffusion term are different from those obtained in the previous papers in their exponential stability conditions. One example is given to illustrate the feasibility of this method in the end.     

Min-max model predictive control for constrained nonlinear systems via multiple LPV embeddings

A min-max model predictive control strategy is proposed for a class of constrained nonlinear system whose trajectories can be embedded within those of a bank of linear parameter varying (LPV) models. The embedding LPV models can yield much better approximation of the nonlinear system dynamics than a single LTV model. For each LPV model, a parameter-dependent Lyapunov function is introduced to obtain poly-quadratically stable control law and to guarantee the feasibility and stability of the original nonlinear system. This approach can greatly reduce computational burden in traditional nonlinear predictive control strategy. Finally a simulation example illustrating the strategy is presented. Supported by the National Natural Science Foundation of China (Grant Nos. 60774015, 60825302, 60674018), the National High-Tech Research & Development Program of China (Grant No. 2007AA041403), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20060248001), and partly by Shanghai Natural Science Foundation (Grant No. 07JC14016)     

Delay-dependent robust H ∞ control for uncertain fuzzy Markovian jump systems

This paper is concerned with the problem of delay-dependent robust H _∞ control for uncertain fuzzy Markovian jump systems with time delays. The purpose is to design a mode-dependent state-feedback fuzzy controller such that the closed-loop system is robustly stochastically stable and satisfies an H _∞ performance level. By introducing slack matrix variables, a delay-dependent sufficient condition for the solvability of the problem is proposed in terms of linear matrix inequalities. An illustrative example is finally given to show the applicability and effectiveness of the proposed method. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. This work is supported by the National Science Foundation for Distinguished Young Scholars of P. R. China under Grant 60625303, the Specialized Research Fund for the Doctoral Program of Higher Education under Grant 20060288021, and the Natural Science Foundation of Jiangsu Province under Grant BK2008047. Yashun Zhang received the B.S. and M.S. degrees in Control Science and Control Engineering from Hefei University of Science and Technology in 2003 and 2006. He is currently a Ph.D. student in Control Science and Control Engineering, Nanjing University of Science and Technology. His research interests include fuzzy control, sliding mode control and nonlinear control. Shengyuan Xu received the Ph.D. degree in Control Science and Control Engineering from Nanjing University of Science and Technology in 1999. His research interests include robust filtering and control, singular systems, time-delay systems and nonlinear systems. Jihui Zhang is a Professor in the School of Automation Engineering of Qingdao University, China. His main areas of interest are discrete event dynamic systems, production planning and control, and operations research.     

Orthogonal Methods Based Ant Colony Search for Solving Continuous Optimization Problems

Research into ant colony algorithms for solving continuous optimization problems forms one of the most significant and promising areas in swarm computation. Although traditional ant algorithms are designed for combinatorial optimization, they have shown great potential in solving a wide range of optimization problems, including continuous optimization. Aimed at solving continuous problems effectively, this paper develops a novel ant algorithm termed ＂continuous orthogonal ant colony＂ （COAC）, whose pheromone deposit mechanisms would enable ants to search for solutions collaboratively and effectively. By using the orthogonal design method, ants in the feasible domain can explore their chosen regions rapidly and efficiently. By implementing an ＂adaptive regional radius＂ method, the proposed algorithm can reduce the probability of being trapped in local optima and therefore enhance the global search capability and accuracy. An elitist strategy is also employed to reserve the most valuable points. The performance of the COAC is compared with two other ant algorithms for continuous optimization -API and CACO by testing seventeen functions in the continuous domain. The results demonstrate that the proposed COAC algorithm outperforms the others.     

On the 2<Superscript>m</Superscript>-variable symmetric Boolean functions with maximum algebraic immunity

The properties of the 2m-variable symmetric Boolean functions with maximum al- gebraic immunity are studied in this paper. Their value vectors, algebraic normal forms, and algebraic degrees and weights are all obtained. At last, some necessary conditions for a symmetric Boolean function on even number variables to have maximum algebraic immunity are introduced.     

A Robust and Fast Non-Local Means Algorithm for Image Denoising

In the paper,we propose a robust and fast image denoising method.The approach integrates both Non- Local means algorithm and Laplacian Pyramid.Given an image to be denoised,we first decompose it into Laplacian pyramid.Exploiting the redundancy property of Laplacian pyramid,we then perform non-local means on every level image of Laplacian pyramid.Essentially,we use the similarity of image features in Laplacian pyramid to act as weight to denoise image.Since the features extracted in Laplacian pyramid are localized in spatial position and scale,they are much more able to describe image,and computing the similarity between them is more reasonable and more robust.Also,based on the efficient Summed Square Image(SSI)scheme and Fast Fourier Transform(FFT),we present an accelerating algorithm to break the bottleneck of non-local means algorithm—similarity computation of compare windows.After speedup,our algorithm is fifty times faster than original non-local means algorithm.Experiments demonstrated the effectiveness of our algorithm.     

Adjoint code generator

The adjoint code generator (ADG) is developed to produce the adjoint codes, which are used to analytically calculate gradients and the Hessian-vector products with the costs independent of the number of the independent variables. Different from other automatic differentiation tools, the implementation of ADG has advantages of using the least program behavior decomposition method and several static dependence analysis techniques. In this paper we first address the concerned concepts and fundamentals, and then introduce the functionality and the features of ADG. In particular, we also discuss the design architecture of ADG and implementation details including the recomputation and storing strategy and several techniques for code optimization. Some experimental results in several applications are presented at the end. Supported by the National Natural Science Foundation of China (Grant Nos. 60503031, 10871014), and the National Basic Research Program of China (Grant No. 2004CB418304)     

Steady-state performance analysis of HOS-based blind adaptive multiuser detection

The blind adaptive multiuser detections based on higher-order statistics (HOS) can obtain higher steady-state decorrelating performance than the conventional linear algorithm under the high SNR condition. However, the closed-form analysis for this steady-state performance is scarce due to the complication of analyzing the nonlinear updates of the adaptive algorithm. An analysis approach based on ordinary differential equation (ODE) method is proposed to get the closed-form excess mean-square error (EMSE) expression of the HOS-based multiuser detections. The simulation and the comparison verify the results of the analysis. Supported by the National Natural Science Foundation of China (Grant No. 60432040), and the Guangxi Natural Science Foundation (Grant Nos. 0731026, 0731025)