This paper addresses the efficient state estimation for mixed linear/nonlinear dynamic systems with noisy measurements. Based on a novel density representation - sliced Gaussian mixture density - the decomposition int...
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ISBN:
(纸本)9783000248832
This paper addresses the efficient state estimation for mixed linear/nonlinear dynamic systems with noisy measurements. Based on a novel density representation - sliced Gaussian mixture density - the decomposition into a (conditionally) linear and nonlinear estimation problem is derived. The systematic approximation procedure minimizing a certain distance measure allows the derivation of (close to) optimal and deterministic estimation results. This leads to high-quality representations of the measurement-conditioned density of the states and, hence, to an overall more efficient estimation process. The performance of the proposed estimator is compared to state-of-the-art estimators, like the well-known marginalized particle filter.
With the increasing number of Web Services with similar or identical functionality, the non-functional properties of a Web Service will become more and more important. Hence, a choice needs to be made to determine whi...
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With the increasing number of Web Services with similar or identical functionality, the non-functional properties of a Web Service will become more and more important. Hence, a choice needs to be made to determine which services are to participate in a given composite service. In general, multi-QoS constrained Web Services composition, with or without optimization, is a NP-complete problem on computational complexity that cannot be exactly solved in polynomial time. A lot of heuristics and approximation algorithms with polynomial- and pseudo-polynomial-time complexities have been designed to deal with this problem. However, these approaches suffer from excessive computational complexities that cannot be used for service composition in runtime. In this paper, we propose a efficient approach for multi-QoS constrained Web Services selection. Firstly, a user preference model was proposed to collect the user's preference. And then, a correlation model of candidate services are established in order to reduce the search space. Based on these two model, a heuristic algorithm is then proposed to find a feasible solution for multi-QoS constrained Web Services selection with highperformance and high precision. The experimental results show that the proposed approach can achieve the expecting goal.
Distributed data mining and in particular grid-enabled data mining has become an active area of research and development in recent years. As the amount of available digital electronic data is growing at an unprecedent...
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ISBN:
(纸本)9780769533056
Distributed data mining and in particular grid-enabled data mining has become an active area of research and development in recent years. As the amount of available digital electronic data is growing at an unprecedented rate, it is necessary to provide general data mining algorithms that help to leverage grid capacity in supporting high-performance distributed computing for solving their data mining problem in a distributed way. In this paper, an optimal multi-strategy based hybrid distribution (ABHD) algorithm based on knowledge grid is proposed for performance improvement over current grid-based association rule mining algorithms. With the optimization polices based on auction model and timestamp mechanism, ABHD algorithm effectively solves the load imbalance problem in grid environment and decreases the communication overhead The response time performance of MBHD algorithm with different numbers of hosts and minimum supports is analyzed by experiments. The numerical results show that ABHD is efficient and performs better than count distribution (CD) algorithm, intelligent data distribution (IDD) algorithm and hybrid distribution (HD) algorithm.
While the demand for memory capacity and performance continues to increase, current DDR memory implementations start to encounter limitations. At high data rates of 533MT/s and above, it becomes increasingly difficult...
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ISBN:
(纸本)9780863419317
While the demand for memory capacity and performance continues to increase, current DDR memory implementations start to encounter limitations. At high data rates of 533MT/s and above, it becomes increasingly difficult to support different combinations of DDR raw card types on the same platform due to the possible variations in load. This paper outlines a method of maximizing the DDR bus performance by utilizing hardware circuitry in the memory controller in connection with softwarealgorithms to adjust the DDR transaction timing relationships based on the populated memory configuration. The algorithm also compensate for the effects of ageing over the lifetime of the part. The techniques used in this work are related to DDR-2 but could also be applicable to DDR-3 and future technologies.
This paper describes a new dynamic evolutionary mechanism which assists process engineers in devising efficient processes for manufacturing high quality items where the mixed production approach is adopted. An adaptiv...
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This paper describes a new dynamic evolutionary mechanism which assists process engineers in devising efficient processes for manufacturing high quality items where the mixed production approach is adopted. An adaptive system, including the use of genetic algorithms (GA) as a dynamic searching mechanism, is designed in order to maximize the stability of the quality control in the mixed production processes. GA is an effective approach in optimization as it is able to alter manufacturing variables so as to reach a global optimum in complex production processes such as multiple quality chains. The choice of the GA operators and its parameters, however, is a significant problem and inappropriate selection of chromosome structure can lead to poor performance. In order to deal with these issues, a dynamic parameter and operator setting approach with a mechanism based on quality control chart theory, is proposed. The approach allows a trade-off between exploration and exploitation processes in the search. The mechanism applies evolution evidence to supervise and adjust the GA parameter settings at run time. A prototype system has been implemented and applied to optimization problems in multiple quality chains. The experimental results have revealed that the dynamic setting approach can improve the performance of a GA process in multiple quality chains. The results also established that the dynamic setting approach is superior to a static one.
The Loongson project is the first attempt to design highperformance general purpose microprocessors in China. It implements a four-issue general purpose RISC microprocessor based on 64-bit MIPS instruction set. Loong...
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ISBN:
(纸本)9781424442331
The Loongson project is the first attempt to design highperformance general purpose microprocessors in China. It implements a four-issue general purpose RISC microprocessor based on 64-bit MIPS instruction set. Loongson-2E is the latest version of the project. highperformance is an important design criterion for Ctyptographic symmetric primitives (include block ciphers and hash functions). This is the first paper which discusses how to optimize AES-128, SHA-256, SHA-512 and Whirlpool algorithms on Loongson-2E. Our programs are, to our best knowledge, the fastest implementations on Loongson-2E. This paper also proposed several new instructions for speedup symmetric primitives and a parallel hash function mode.
This work proposes a method to fine grain the ranking of solutions after they have been ranked by Pareto dominance, aiming to improve the performance of evolutionary algorithms oil many objective's optimization pr...
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ISBN:
(纸本)9783540896937
This work proposes a method to fine grain the ranking of solutions after they have been ranked by Pareto dominance, aiming to improve the performance of evolutionary algorithms oil many objective's optimization problems. The re-ranking method uses a randomized sampling procedure to choose, from sets of equally ranked solutions, those solutions that, will be given selective advantage,. The sampling procedure favors a good distribution of the, sampled solutions based on dominance regions wider than conventional Pareto dominance. We enhance, NSGA-II with the proposed method and test its performance on with up to M = 10 objectives. Experimental result's show that, convergence and diversity of the solutions found call improve remarkably oil 3 <= M <= 10 objectives problems.
Many videotexts exist in TV programs. Some videotexts provide valuable information. Thus, an efficient design to extract these videotexts is requested. Existing videotext extractors work on the PC platform and they ar...
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ISBN:
(纸本)9781424440993
Many videotexts exist in TV programs. Some videotexts provide valuable information. Thus, an efficient design to extract these videotexts is requested. Existing videotext extractors work on the PC platform and they are difficult to achieve real-time extraction and integration. Therefore, this work designs a videotext extractor on a dual-core platform. A distributed design framework for a dual-core platform is proposed. The extraction task is dispatched to the ARM and the DSP. The ARM core executes capture, display, control, and extraction threads. The DSP core performs algorithms. The ARM and the DSP communicate by buffers and solid channels. On the DSP side, some techniques are manipulated to optimize the videotext extractor. They include software pipeline, internal memory, adjusted program, assembly optimization, and DMA. To achieve highperformance, two transferred schemes of DMA are proposed. This system is implemented on the TI Davinci DM6446 platform. All input videos are 720 x 480 with 30 fps captured from real-time DVB-T system. The simulation result shows that this extractor can process the large-size frames, and all the videotext can be extracted. With this novel architecture, the extraction speed can be enhanced to 23 frames per second.
The rate-distortion optimization (RDO) technique is employed in H.264/AVC intra frame coding to achieve the best rate-distortion performance. But the computational complexity is very high because it encodes the curren...
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In this paper, we examine the data replication problem in a particular grid delivery network (GDN). In this system, the data are divided into fixed size blocks which must be replicated on hosts to decrease the total d...
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In this paper, we examine the data replication problem in a particular grid delivery network (GDN). In this system, the data are divided into fixed size blocks which must be replicated on hosts to decrease the total download time. We propose a probabilistic model to optimize the average download time of requests based on the hosts availability and the document size distribution. The objective function induced by this model is a nonlinear integer problem. It can be solved in real values by Lagrangian optimization. We prove that in a particular case, this problem can be reduced to a knapsack problem. We propose approximation algorithms and validate them using simulations with varying characteristics.
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