A novel dual-min-sum decoding algorithm for low-density parity-check codes is proposed. The proposed algorithm simplifies the check-node updates and thus reduces the computational complexity of the belief propagation ...
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A novel dual-min-sum decoding algorithm for low-density parity-check codes is proposed. The proposed algorithm simplifies the check-node updates and thus reduces the computational complexity of the belief propagation (BP) algorithm significantly. Simulation results show that the proposed algorithm can achieve an error performance very close to that of the BP algorithm.
The article focuses on distributed rendering environments (DREs) for teaching animation and scientific visualization. Most DREs are deployed in tightly controlled animation production units or national labs where acce...
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The article focuses on distributed rendering environments (DREs) for teaching animation and scientific visualization. Most DREs are deployed in tightly controlled animation production units or national labs where access is limited to a small group of people. While DREs are well known in the industry, no implementations are currently available for general student access. Furthermore, the challenges of setting up such a system for a large audience of students at colleges and universities are significant. Given this scenario, computer graphics students today have no exposure to real-world problem-solving techniques in rendering and animation development, as that would require access to an infrastructure that is absent in academia. As rendering algorithms are continuously refined to maximize accuracy and clarity of animations and scientific visualizations, the computational resources required to achieve this objective have also increased exponentially. It's impractical for educational institutions to invest valuable dollars in infrastructure that can only be used for rendering. However, most universities support and maintain large computer laboratories that remain unused for a small part of each day. INSET: Background and Rationale..
A new approach to control the speed and rotor flux of an induction motor using the theory of the sliding-mode is presented. Sabanovic's equations for an induction motor are first modified to a state space form sui...
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A new approach to control the speed and rotor flux of an induction motor using the theory of the sliding-mode is presented. Sabanovic's equations for an induction motor are first modified to a state space form suitable for the present design of the algorithm. For controlling the speed and rotor flux of the drive, a simple control algorithm is proposed based on the existence of a certain positive definite matrix. Lyapunov direct method is used to ensure the reaching and sustaining of sliding-mode. Obviation of flux measurement is achieved through manipulation of Stanley's equations. Simulation studies are conducted. The control algorithm exhibits excellent drive performance in the presence of load disturbances and stator and rotor resistances changes up to 100% of the nominal values.
In this paper, we use the Exp-function method to construct the generalized solitary wave solutions of the generalized (1 + 1)-dimensional and the generalized (2 + 1)-dimensional Ito equations. These equations play a v...
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In this paper, we use the Exp-function method to construct the generalized solitary wave solutions of the generalized (1 + 1)-dimensional and the generalized (2 + 1)-dimensional Ito equations. These equations play a very important role in mathematical physics and engineering sciences. The suggested algorithm is quite efficient and is practically well suited for use in these problems. The results show the reliability and efficiency of the proposed method. Finally, some new solitonary wave solutions are obtained. (C) 2008 Elsevier Ltd. All rights reserved.
A deterministic parallel LL parsing algorithm is presented. The algorithm is based on a transformation from a parsing problem to parallel reduction. First, a nondeterministic version of a parallel LL parser is introdu...
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A deterministic parallel LL parsing algorithm is presented. The algorithm is based on a transformation from a parsing problem to parallel reduction. First, a nondeterministic version of a parallel LL parser is introduced. Then, it is transformed into the deterministic version-the LLP parser. The deterministic LLP(q,k) parser uses two kinds of information to select the next operation - a lookahead string of length up to k symbols and a lookback string of length up to q symbols. Deterministic parsing is available for LLP grammars, a subclass of LL grammars. Since the presented deterministic and nondeterministic parallel parsers are both based on parallel reduction, they are suitable for most parallel architectures.
An implicit reserve constraint unit commitment (IRCUC) model is presented in this paper. Different from the traditional unit commitment (UC) model, the constraint of spinning reserve is not given explicitly but implic...
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An implicit reserve constraint unit commitment (IRCUC) model is presented in this paper. Different from the traditional unit commitment (UC) model, the constraint of spinning reserve is not given explicitly but implicitly in a trade-off between the production cost and the outage loss. An analytical method is applied to evaluate the reliability of UC solutions and to estimate the outage loss. The stochastic failures of generating units and uncertainties of load demands are considered while assessing the reliability. The artificial fish swarm algorithm(AFSA) is employed to solve this proposed model. In addition to the regular operation, a mutation operator (MO) is designed to enhance the searching performance of the algorithm. The feasibility of the proposed method is demonstrated from 10 to 100 units system, and the testing results are compared with those obtained by genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) in terms of total production cost and computational time. The simulation results show that the proposed method is capable of obtaining higher quality solutions.
The use of hybrid algorithms for solving real-world optimization problems has become popular since their solution quality can be made better than the algorithms that form them by combining their desirable features. Th...
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The use of hybrid algorithms for solving real-world optimization problems has become popular since their solution quality can be made better than the algorithms that form them by combining their desirable features. The newly proposed hybrid method which is called Hybrid Differential, Particle, and Harmony (HDPH) algorithm is different from the other hybrid forms since it uses all features of merged algorithms in order to perform efficiently for a wide variety of problems. In the proposed algorithm the control parameters are randomized which makes its implementation easy and provides a fast response. This paper describes the application of HDPH algorithm to linear antenna array synthesis. The results obtained with the HDPH algorithm are compared with three merged optimization techniques that are used in HDPH. The comparison shows that the performance of the proposed algorithm is comparatively better in both solution quality and robustness. The proposed hybrid algorithm HDPH can be an efficient candidate for real-time optimization problems since it yields reliable performance at all times when it gets executed.
Based on an internal tidal model, the practical performances of the limited-memory BFGS (L-BFGS) method and two gradient descent (GD) methods (the normal one with Wolfe's line search and the simplified one) are in...
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Based on an internal tidal model, the practical performances of the limited-memory BFGS (L-BFGS) method and two gradient descent (GD) methods (the normal one with Wolfe's line search and the simplified one) are investigated computationally through a series of ideal experiments in which the open boundary conditions (OBCs) are inverted by assimilating the interior observations with the adjoint method. In the case that the observations closer to the unknown boundary are included for assimilation, the L-BFGS method performs the best. As compared with the simplified GD method, the normal one really uses less iteration to reach a satisfactory solution, but its advantage over the simplified one is much smaller than expected. In the case that only the observations that are further from the unknown boundary are assimilated, the simplified GD method performs the best instead, whereas the performances of the other two methods are not satisfactory. The advanced L-BFGS algorithm and Wolfe's line search still need to be improved when applied to the practical cases. The simplified GD method, which is controllable and easy to implement, should be regarded seriously as a choice, especially when the classical advanced optimization techniques fail or perform poorly.
As networks become pervasive, the importance of efficient information gathering for purposes such as monitoring, fault diagnosis, and performance evaluation increases. Distributed monitoring systems based on either ma...
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As networks become pervasive, the importance of efficient information gathering for purposes such as monitoring, fault diagnosis, and performance evaluation increases. Distributed monitoring systems based on either management protocols such as SNMP or distributed object technologies such as CORBA can cope with scalability problems only to a limited extent. They are not well suited to systems that are both very large and highly dynamic because the monitoring logic, although possibly distributed, is statically predefined at design time. This article presents an active distributed monitoring system based on mobile agents. Agents act as area monitors not bound to any articular network node that can "sense" the network, estimate better locations, and migrate in order to pursue location optimality. Simulations demonstrate the capability of this approach to cope with large-scale systems and changing network conditions.
An integrated approach to the design of practical adaptive control algorithms is presented. Many existing ideas are brought together, and the effect of various design parameters available to a user is explored. The th...
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An integrated approach to the design of practical adaptive control algorithms is presented. Many existing ideas are brought together, and the effect of various design parameters available to a user is explored. The theory is extended by showing how the problem of stabilizability of the estimated model can be overcome by running parallel estimators. It is shown how asymptotic tracking of deterministic set points can be achieved in the presence of unmodeled dynamics.
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