Consideration was given to the problem of controlling a linear plant with bounded disturbances at input and output and unmeasurable controlled parameters. A control algorithm to satisfy the target condition and compen...
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Consideration was given to the problem of controlling a linear plant with bounded disturbances at input and output and unmeasurable controlled parameters. A control algorithm to satisfy the target condition and compensate the disturbances was proposed. A numerical example and the results of computer-aided simulation were presented.
For an undirected complex network made up with vertices and edges, we developed a fast computing algorithm that divides vertices into different groups by maximizing the standard "modularity" measure of the r...
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For an undirected complex network made up with vertices and edges, we developed a fast computing algorithm that divides vertices into different groups by maximizing the standard "modularity" measure of the resulting partitions. The algorithm is based on a simple constrained power method which maximizes a quadratic objective function while satisfying given linear constraints. We evaluated the performance of the algorithm and compared it with a number of state-of-the-art solutions. The new algorithm reported both high optimization quality and fast running speed, and thus it provided a practical tool for community detection and network structure analysis.
An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work int...
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An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work intends to bring to natural language processing research, the use of a more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may bring an increase in computational efficiency when compared to the sa-called biologically implausible algorithms.
Linearization, interpolation and end-point constraints are combined to derive a receding horizon predictive control algorithm for continuous-time non-linear systems which are subject to input constraints. The algorith...
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Linearization, interpolation and end-point constraints are combined to derive a receding horizon predictive control algorithm for continuous-time non-linear systems which are subject to input constraints. The algorithm makes extensive use of the 'tail' of input/output state trajectories, namely the extension to current time of trajectories computed at the previous time instant. Through this device, the algorithm has guaranteed feasibility and stability and has some desirable attributes with respect to dynamic performance. The results of the paper are illustrated by a model of a coupled tank system.
This article proposes a new filter for interferometric synthetic aperture radar (InSAR) phase denoising. Traditional phase filters generally face two major challenges: to preserve texture details while reducing noise ...
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This article proposes a new filter for interferometric synthetic aperture radar (InSAR) phase denoising. Traditional phase filters generally face two major challenges: to preserve texture details while reducing noise and to perform well in less time. The local linear model-based guided filter and Stein's unbiased risk estimate (SURE)-based filter, in contrast, have a high quality of edge-preserving performance and high efficiency owing to the feature of SURE formula and simplicity. Nevertheless, as these filters are designed for general digital images, they are not suitable for periodic and high-noise-level interferometric phase images. In this article, we modified the original filters by considering the coherence coefficient and features of the interferometric phase image, creating a new patch-based filter adapted to areas characterized by different coherences. Moreover, after obtaining the solution of a patch, considering the geometric closeness and the phasic similarity, we used a bilateral filter combining the pixels in the patch to obtain the estimate. Experimental results based on the simulated and real data confirmed the effectiveness of the proposed algorithm.
The modified Hamiltonian Monte Carlo (MHMC) methods, i.e., importance sampling methods that use modified Hamiltonians within a Hybrid Monte Carlo (HMC) framework, often outperform in sampling efficiency standard techn...
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The modified Hamiltonian Monte Carlo (MHMC) methods, i.e., importance sampling methods that use modified Hamiltonians within a Hybrid Monte Carlo (HMC) framework, often outperform in sampling efficiency standard techniques such as molecular dynamics (MD) and HMC. The performance of MHMC may be enhanced further through the rational choice of the simulation parameters and by replacing the standard Verlet integrator with more sophisticated splitting algorithms. Unfortunately, it is not easy to identify the appropriate values of the parameters that appear in those algorithms. We propose a technique, that we call MAIA (Modified Adaptive Integration Approach), which, for a given simulation system and a given time step, automatically selects the optimal integrator within a useful family of two-stage splitting formulas. Extended MAIA (or e-MAIA) is an enhanced version of MAIA, which additionally supplies a value of the method-specific parameter that, for the problem under consideration, keeps the momentum acceptance rate at a user-desired level. The MAIA and e-MAIA algorithms have been implemented, with no computational overhead during simulations, in MultiHMC-GROMACS, a modified version of the popular software package GROMACS. Tests performed on well-known molecular models demonstrate the superiority of the suggested approaches over a range of integrators (both standard and recently developed), as well as their capacity to improve the sampling efficiency of GSHMC, a noticeable method for molecular simulation in the MHMC family. GSHMC combined with e-MAIA shows a remarkably good performance when compared to MD and HMC coupled with the appropriate adaptive integrators.
A novel chaotic hash algorithm based on a network structure formed by 16 chaotic maps is proposed. The original message is first padded with zeros to make the length a multiple of four. Then it is divided into a numbe...
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A novel chaotic hash algorithm based on a network structure formed by 16 chaotic maps is proposed. The original message is first padded with zeros to make the length a multiple of four. Then it is divided into a number of blocks each contains 4 bytes. In the hashing process, the blocks are mixed together by the chaotic map network since the initial value and the control parameter of each tent map are dynamically determined by the output of its neighbors. To enhance the confusion and diffusion effect, the cipher block chaining (CBC) mode is adopted in the algorithm. Theoretic analyses and numerical simulations both show that the proposed hash algorithm possesses good statistical properties, strong collision resistance and high flexibility, as required by practical keyed hash functions. (C) 2008 Elsevier Ltd. All rights reserved.
Visual Determination of the Opacity of Emissions from Stationary Sources (Method 9) is a reference method established by U.S. Environmental Protection Agency (EPA) to quantify plume opacity. However, Method 9 relies o...
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Visual Determination of the Opacity of Emissions from Stationary Sources (Method 9) is a reference method established by U.S. Environmental Protection Agency (EPA) to quantify plume opacity. However, Method 9 relies on observations from humans, which introduces subjectivity. In addition, it is expensive to teach and certify personnel to evaluate plume opacity on a semiannual basis. In this study, field tests were completed during a "smoke school" and a 4-month monitoring program of plumes emitted from stationary sources with a Method 9 qualified observer to evaluate the use of digital photography and two computer algorithms as an alternative to Method 9. This Digital Optical Method (DOM) improves objectivity, costs less to implement than Method 9, and provides archival photographic records of the plumes. Results from "smoke school" tests indicate that DOM passed six of eight tests when the sun was located in the 140 degrees sector behind one of the three cameras, with the individual opacity errors of 15% or less and average opacity errors of 7.5% or less. DOM also passed seven of the eight tests when the sun was located in the 216 degrees sector behind another camera. However, DOM passed only one of the eight tests when the sun was located in the 116 degrees sector in front of the third camera. Certification to read plume opacity by a "smoke reader" for 6 months requires that the "smoke reader" pass one of the smoke school tests during smoke school. The average opacity errors and percentage of observations with individual opacity errors above 15% for the results obtained with DOM were lower than those obtained by the smoke school trainees with the sun was located behind the camera, whereas they were higher than the smoke school trainee results with the sun located in front of the camera. In addition, the difference between plume opacity values obtained by DOM and a Method 9 qualified observer, as measured in the field for two industrial sources, were 2.2%. These enc
Data congestion and network delay are the important factors that affect performance of cloud computing systems. Using local disk of computing nodes as a cache can sometimes get better performance than accessing data t...
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Data congestion and network delay are the important factors that affect performance of cloud computing systems. Using local disk of computing nodes as a cache can sometimes get better performance than accessing data through the network. This paper presents a storage cache placement algorithm-C-Aware, which traces history access information of cache and data source, adaptively decides whether to cache data according to cache media characteristic and current access environment, and achieves good performance under different workload on storage server. We implement this algorithm in both simulated and real environments. Our simulation results using OLTP and WebSearch traces demonstrate that C-Aware achieves better adaptability to the changes of server workload. Our benchmark results in real system show that, in the scenario where the size of local cache is half of data set, C-Aware gets nearly 80% improvement compared with traditional methods when the server is not busy and still presents comparable performance when there is high workload on server side.
Holographic algorithms with matchgates are a novel approach to design polynomial time computation. They use Kasteleyn's algorithm for perfect matchings, and more importantly a holographic reduction. The two fundam...
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Holographic algorithms with matchgates are a novel approach to design polynomial time computation. They use Kasteleyn's algorithm for perfect matchings, and more importantly a holographic reduction. The two fundamental parameters of a holographic reduction are the domain size k of the underlying problem and the basis size l. A holographic reduction transforms the computation to matchgates by a linear transformation that maps to (a tensor product space of) a linear space of dimension 2(l). We prove a sharp basis collapse theorem, which shows that for domain size 3 and 4, all non-trivial holographic reductions can be expressed with a basis of size 1 or 2, respectively. The main proof techniques are Matchgate Identities and a Group Property of matchgate signatures. (C) 2014 Elsevier Inc. All rights reserved.
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