The existing transportation service system in public travel route can not satisfy the people's actual travel need because of various technologies reasons. In our study, we set the tourist attractions as a vertex, ...
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ISBN:
(纸本)9783037853801
The existing transportation service system in public travel route can not satisfy the people's actual travel need because of various technologies reasons. In our study, we set the tourist attractions as a vertex, and simplified the traditional algorithm for complex network computing. Aim to improve the disadvantage of tradition Dijkstra algorithm, an improve algorithm was proposed to improve the path search efficiency. Then the improved Dijkstra algorithm was applied to tourism path search. The experimental results have illustrated that the improved Dijkstra algorithm can accomplish a better result and improve path search efficiency.
With the increasingly growing amount of service requests from the world-wide customers, the cloud systems is capable of providing services while meeting the customers' satisfaction. Recently, to achieve the better...
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ISBN:
(纸本)9780769550886
With the increasingly growing amount of service requests from the world-wide customers, the cloud systems is capable of providing services while meeting the customers' satisfaction. Recently, to achieve the better reliability and performance, the cloud systems has been largely depending on the geographically distributed data centers. Nevertheless, the dollar cost of service placement by service providers (SP) differ from the multiple regions. Accordingly, it is crucial to design a request dispatching and resource allocation algorithm to maximize net profit. The existing algorithms are either built upon energy-efficient schemes alone, or multi-type requests and customer satisfaction oblivious. They cannot be applied to multi-type requests and customer satisfaction-aware algorithm design with the objective of maximizing net profit. This paper proposes a customer satisfaction-aware algorithm based on the Ant-Colony Optimization (AMP) for geo-distributed data centers. By introducing the model of customer satisfaction, we formulate the utility (or net profit) maximization issue as an optimization problem under the constraints of customer satisfaction and data centers. AMP maximizes SP net profit by dispatching service requests to the proper data centers and generating the appropriate amount of Virtual Machines (VMs) to meet customer satisfaction. To evaluate the proposed algorithm, we have conducted the comprehensive simulation and compared with the other state-of-the-art algorithms. Conclusive results have demonstrated the effectiveness of AMP both in small and large scale problem.
Matlab is one of the popular softwares for designing algorithms in scientific researches. Based on the case about calculating similarity matrix, which often occurs in our researches, this paper discusses fast methods ...
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Matlab is one of the popular softwares for designing algorithms in scientific researches. Based on the case about calculating similarity matrix, which often occurs in our researches, this paper discusses fast methods for dealing with large scale data(matrix) from theoretical analysis and algorithm design, and obtains efficient algorithms. By analyzing the case described above, we can develop various abilities of graduate students: mathematical thinking and use, algorithm design. This teaching case can also improve their study and work efficiency.
The paper presents an algorithm for the design of a single functional observer for a linear time-varying system. The proposed constructive procedure can be iterated to obtain a minimal order for the observer where the...
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ISBN:
(纸本)9781467357159
The paper presents an algorithm for the design of a single functional observer for a linear time-varying system. The proposed constructive procedure can be iterated to obtain a minimal order for the observer where the existence conditions are fufilled. As a specific feature, this procedure does not require the solution of any differential Sylvester equation.
In this paper, we address the problem of designing probabilistic robust controllers for discrete-time systems whose objective is to reach and remain in a given target set with high probability. More precisely, given p...
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ISBN:
(纸本)9781467357159
In this paper, we address the problem of designing probabilistic robust controllers for discrete-time systems whose objective is to reach and remain in a given target set with high probability. More precisely, given probability distributions for the initial state, uncertain parameters and disturbances, we develop algorithms for designing a control law that i) maximizes the probability of reaching the target set in N steps and ii) makes the target set robustly positively invariant. As defined the problem is nonconvex. To solve this problem, a sequence of convex relaxations is provided, whose optimal value is shown to converge to solution of the original problem. In other words, we provide a sequence of semidefinite programs of increasing dimension and complexity which can arbitrarily approximate the solution of the probabilistic robust control design problem addressed in this paper. Two numerical examples are presented to illustrate preliminary results on the numerical performance of the proposed approach.
In this article a new algorithm for the design of stationary input sequences for system identification is presented. The stationary input signal is generated by optimizing an approximation of a scalar function of the ...
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ISBN:
(纸本)9781467357159
In this article a new algorithm for the design of stationary input sequences for system identification is presented. The stationary input signal is generated by optimizing an approximation of a scalar function of the information matrix, based on stationary input sequences generated from prime cycles, which describe the set of finite Markov chains of a given order. This method can be used for solving input design problems for nonlinear systems. In particular it can handle amplitude constraints on the input. Numerical examples show that the new algorithm is computationally attractive and that is consistent with previously reported results.
A novel algorithm called Cooperative Binary Iterative Hard Thresholding (CB-IHT) based on distributed 1-bit compressive sensing is proposed in this paper. Taking advantage of the correlated nature of distributed signa...
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ISBN:
(纸本)9781479903085
A novel algorithm called Cooperative Binary Iterative Hard Thresholding (CB-IHT) based on distributed 1-bit compressive sensing is proposed in this paper. Taking advantage of the correlated nature of distributed signal processing, the proposed algorithm is aimed to fight against the error floor in the estimation of distorted sparse signal, with an array of agents recovering the target signal cooperatively. The principles of convex optimization, consistent reconstruction and greedy pursuit algorithm are combined in the algorithm design. With two joint sparsity models representing distortion of equivalent parallel AWGN channels and parallel fading channels separately, the algorithm is performed through extensive simulations, which show that with severe distortion and large bit-budget, estimation accuracy can be improved by simply increasing the array scale.
Recent results have shown that interference alignment (IA) achieves the optimal throughput scaling law w.r.t. SNR. However, except for a few special cases, finding transceivers to achieve IA in MIMO interference netwo...
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ISBN:
(纸本)9781479913510
Recent results have shown that interference alignment (IA) achieves the optimal throughput scaling law w.r.t. SNR. However, except for a few special cases, finding transceivers to achieve IA in MIMO interference networks is still an open problem. This problem is challenging due to the non-convex nature of the interference optimization problem. Inspired by recent success in using tools from algebraic geometry to analyze the feasibility conditions of IA, in this work, we adopt algebraic geometry analysis to guide IA algorithm design. Specifically, we first explore the relation between algebraic independence and feasibility of polynomial equation sets, and transform the IA problem into an equivalent polynomial form, whose policy space is convex. Then we reformulate the transformed IA problem into an interference optimization problem. By exploiting the connection between algebraic independence and full rankness of Jacobian matrix, we prove that in the interference optimization problem, there is no performance gap between local and global optimums when IA is feasible. This property enables us to easily design IA algorithms by adopting existing local search algorithms. Combining the propositions obtained in this work and those obtained in the authors' prior work on IA feasibility, we have established a unified algebraic framework for both IA feasibility analysis and algorithm design.
This work presents an algorithm for designing the optimal robust saturated output feedback controller for the two-link planar robot with a spring between two links by the Attractive Ellipsoid Method serving for class ...
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ISBN:
(纸本)9781467357159
This work presents an algorithm for designing the optimal robust saturated output feedback controller for the two-link planar robot with a spring between two links by the Attractive Ellipsoid Method serving for class of uncertain "quasi-Lipschitz" dynamics. The Attractive Ellipsoid Method (AEM) application permits to describe the class of nonlinear feedbacks containing a saturation operator that guarantees a boundedness of all possible trajectories around the origin. Here we consider more general types of nonlinear bounded feedbacks which can be corrected (adjusted) on-line during a control process. The optimization of feedback within this class of controllers is associated with the selection of the feedback parameters which provide the trajectory converges within an ellipsoid of a "minimal size".
We present Geospatial Intelligence (GEOINT) as a context for computing education. GEOINT is a rich source of ideas for programming projects, algorithm design and use of databases. Students are interested in GEOINT due...
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ISBN:
(纸本)9781450318686
We present Geospatial Intelligence (GEOINT) as a context for computing education. GEOINT is a rich source of ideas for programming projects, algorithm design and use of databases. Students are interested in GEOINT due to its inherently visual subject matter and its strong ties with crime, espionage and social changes and upheavals. In short we are motivating computation as a subject that can provide solutions and insights into crime mysteries and complex events that unfold over time and space. In addition to keeping Computer Science majors interested, we also seek to attract students of other disciplines into computing. GEOINT and computing knowledge can provide initial preparation for certain jobs that are in demand and also for graduate school. Our assignments and programming projects that are inspired by GEOINT can be used in an introductory programming course or a more advanced course. These materials derive from well known case studies and also fundamentals concepts in computing. Some programming projects are based on exploration of chronologies and timelines as tools that enable the geographical display of information as an order sequence of events. In general these geospatial displays can correlate information to help correct for possible gaps and inconsistencies in knowledge. These materials use multiple layered techniques of presenting information that use time, geographical location, weather conditions and static features of the earth's surface.
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