This paper considers allocation of space in a hnear storage medium when space must be allocated dynamically as customers arrive A heuristic is proposed for this problem and for a simple model of the resultmg reference...
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Presents convex hulls of sets of points in two and three dimensions. Relevance of the convex hull on several problems in computer graphics, design automation, pattern recognition and operations research; Technique use...
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Presents convex hulls of sets of points in two and three dimensions. Relevance of the convex hull on several problems in computer graphics, design automation, pattern recognition and operations research; Technique used in the algorithm.
An indirect adaptive control algorithm for a MIMO plant is studied. It is shown that Polyak - Ruppert estimation algorithm along with the simple dead-beat control law constitutes an adaptive control strategy that achi...
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An indirect adaptive control algorithm for a MIMO plant is studied. It is shown that Polyak - Ruppert estimation algorithm along with the simple dead-beat control law constitutes an adaptive control strategy that achieves the highest possible rate of convergence for the quadratic criterion.
We study parallel algorithms for a number of graph problems, using the Single Instruction Stream-Multiple Data Stream model. We assume that the processors have access to a common memory and that no memory or data alig...
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We study parallel algorithms for a number of graph problems, using the Single Instruction Stream-Multiple Data Stream model. We assume that the processors have access to a common memory and that no memory or data alignment time penalties are incurred. We derive a general time bound for a parallel algorithm that uses K processors for finding the connected components of an undirected graph. In particular, an O(log² n) time bound can be achieved using only K = n[n/log² n] processors. This result is optimal in the sense that the speedup ratio is linear with the number of processors used. The algorithm can also be modified to solve a whole class of graph problems with the same time bound and fewer processors than previous parallel methods. [ABSTRACT FROM AUTHOR]
Iterations for solving the nonhnear equation F(x) = 0 in N-dimensional Banach space, [formula omitted], which use “integral mformatton with a kernel” are considered This information consists of the “standard reform...
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Due to its attractive topological properties, the hypercube multiprocessor has emerged as one of the architectures of choice when it comes to implementing a large number of computational problems. In many such applica...
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ISBN:
(纸本)9780897915069
Due to its attractive topological properties, the hypercube multiprocessor has emerged as one of the architectures of choice when it comes to implementing a large number of computational problems. In many such applications, Gray-code labelings of the hypercube are a crucial prerequisite for obtaining efficient algorithms. We propose a greedy algorithm that, given an n-dimensional hypercube H with N=2n nodes, returns a Gray-code labeling of H , that is, a labeling of the nodes with binary strings of length n such that two nodes are neighbors in the hypercube if, and only if, their labels differ in exactly one bit. Our algorithm is conceptually very simple and runs in O(Nlog N) time being, therefore, optimal. As it turns out, with a few modifications our labeling algorithm can be used to recognize hypercubes as well.
The concept of forwarding sets is widely adopted in many broadcast protocols for wireless multihop networks to alleviate the broadcast storm problem. In these protocols, after receiving a broadcast message, each node ...
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The concept of forwarding sets is widely adopted in many broadcast protocols for wireless multihop networks to alleviate the broadcast storm problem. In these protocols, after receiving a broadcast message, each node that is requested to relay the message instructs a subset of its 1-hop neighbors, a.k.a. the forwarding set, to further relay it. In this paper, we propose to use the Minimum Local Disk Cover Set (MLDCS) as the forwarding set in heterogeneous multihop wireless networks, where nodes may have different transmission ranges. We show that the minimum local disk cover set of a node in heterogeneous networks is equivalent to its skyline set, and then we propose a divide-and-conquer algorithm with the optimal time complexity to compute the skyline set locally and statelessly. Moreover, unlike other forwarding heuristics, the proposed algorithm requires only 1-hop neighbor information. This helps to reduce the forwarding set formation latency and thus will be more suitable for environments with a frequently changed network topology, such as vehicular ad hoc networks.
Domino logic is one of the most popular dynamic circuit configurations for implementing high-performance logic designs. Since domino logic is inherently noninverting, it presents a fundamental constraint of implementi...
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ISBN:
(纸本)9780818675973
Domino logic is one of the most popular dynamic circuit configurations for implementing high-performance logic designs. Since domino logic is inherently noninverting, it presents a fundamental constraint of implementing logic functions without any intermediate inversions. Removal of intermediate inverters requires logic duplication for generating both the negative and positive signal phases, which results in significant area overhead. This area overhead can be substantially reduced by selecting an optimal output phase assignment, which results in a minimum logic duplication penalty for obtaining inverter-free logic. In this paper, we present this previously unaddressed problem of output phase assignment for minimum area duplication in dynamic logic synthesis. We give both optimal and heuristic algorithms for minimizing logic duplication.
The establishment of lower bounds on the number of comparisons necessary to solve various combinatorial problems is considered. Some of the new results are : (a) given two finite sets of real numbers, A and B, where n...
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This paper takes a close look at the important commonalities and subtle differences between the well-established field of supervised learning and the much younger one of cooptimization. It explains the relationships b...
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This paper takes a close look at the important commonalities and subtle differences between the well-established field of supervised learning and the much younger one of cooptimization. It explains the relationships between the problems, algorithms and views on cost and performance of the two fields, all throughout providing a two-way dictionary for the respective terminologies used to describe these concepts. The intent is to facilitate advancement of both fields through transfer and cross-pollination of ideas, techniques and results. As a proof of concept, a theoretical study is presented on the connection between existence / lack of free lunch in the two fields, showcasing a few ideas for improving computational complexity of certain supervised learning approaches.
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