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Minimum energy mobile wireless networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 1999
"... We describe a distributed positionbased network protocol optimized for minimum energy consumption in mobile wireless networks that support peertopeer communications. Given any number of randomly deployed nodes over an area, we illustrate that a simple local optimization scheme executed at each n ..."
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Cited by 749 (0 self)
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node guarantees strong connectivity of the entire network and attains the global minimum energy solution for stationary networks. Due to its localized nature, this protocol proves to be selfreconfiguring and stays close to the minimum energy solution when applied to mobile networks. Simulation results
The inverse source problem of electromagnetics: Linear inversion formulation and minimum energy solution
 IEEE Trans. Antennas Propag
, 1999
"... Abalmcl We address an inverse source problem consisting of flnding the timeharmonic current distribution (source) with minimum Lz norm (minimum cnergy) that generates a prescribed electromagnetic fleld provided outside the source's support. Using the wellknown multipole expansion of the elect ..."
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Cited by 20 (13 self)
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Abalmcl We address an inverse source problem consisting of flnding the timeharmonic current distribution (source) with minimum Lz norm (minimum cnergy) that generates a prescribed electromagnetic fleld provided outside the source's support. Using the wellknown multipole expansion
The Inverse Source Problem of Electromagnetics: Linear Inversion Formulation and Minimum Energy Solution
"... the mode occurs at �™�� � aSGHz. Fig. 2(a) ( � aIHGHz) and Fig. 2(b) ( � aPGHz), show the radiated field for frequencies above and below the cutoff, respectively. In both cases, the line integration (continuous line) and the surface integrations (dots) lead to identical results in the limit of the ..."
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the mode occurs at �™�� � aSGHz. Fig. 2(a) ( � aIHGHz) and Fig. 2(b) ( � aPGHz), show the radiated field for frequencies above and below the cutoff, respectively. In both cases, the line integration (continuous line) and the surface integrations (dots) lead to identical results in the limit of the numerical precision. In conclusion, the rigorous derivation of surface integral into line integral presented here provides an evident gain of CPU time with respect to a conventional aperture integration, especially for higher order modes and large aperture in terms of the wavelength. No numerical integration problems are detected and significant advantages in the numerical stability of the integration is obtained for observation points close to the aperture. Furthermore, the interpretation of the rim integrand in terms of elementary Maxwellian sources of spherical waves could be useful to approximating the interaction of the aperture with other structures (i.e., edges of the flange), when these sources are forced to radiate with an appropriate Green’s function. This aspect is under investigation.
A scheduling model for reduced CPU energy
 ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE
, 1995
"... The energy usage of computer systems is becoming an important consideration, especially for batteryoperated systems. Various methods for reducing energy consumption have been investigated, both at the circuit level and at the operating systems level. In this paper, we propose a simple model of job s ..."
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Cited by 558 (3 self)
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an offline algorithm that computes, for any set of jobs, a minimumenergy schedule. We then consider some online algorithms and their competitive performance for the power function P(s) = sp where p 3 2. It is shown that one natural heuristic, called the Average Rate heuristic, uses at most a constant
Fast approximate energy minimization via graph cuts
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2001
"... In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function’s smoothness term must only involve pairs of pixels. We propose two algorithms that use graph cuts to compute a local minimum even when v ..."
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Cited by 2120 (61 self)
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In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function’s smoothness term must only involve pairs of pixels. We propose two algorithms that use graph cuts to compute a local minimum even when
Energyefficient communication protocol for wireless microsensor networks
, 2000
"... Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our f ..."
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Cited by 2103 (10 self)
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findings that the conventional protocols of direct transmission, minimumtransmissionenergy, multihop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (LowEnergy Adaptive Clustering Hierarchy), a clusteringbased protocol that utilizes randomized rotation of local
Guaranteed minimumrank solutions of linear matrix equations via nuclear norm minimization,”
 SIAM Review,
, 2010
"... Abstract The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the literature of a diverse set of fields including system identification and control, Euclidean embedding, and col ..."
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Cited by 562 (20 self)
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for the linear transformation defining the constraints, the minimum rank solution can be recovered by solving a convex optimization problem, namely the minimization of the nuclear norm over the given affine space. We present several random ensembles of equations where the restricted isometry property holds
Energy Conserving Routing in Wireless Adhoc Networks
, 2000
"... An adhoc network of wireless static nodes is considered as it arises in a rapidly deployed, sensor based, monitoring system. Information is generated in certain nodes and needs to reach a set of designated gateway nodes. Each node may adjust its power within a certain range that determines the set ..."
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Cited by 622 (2 self)
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the set of possible one hop away neighbors. Traffic forwarding through multiple hops is employed when the intended destination is not within immediate reach. The nodes have limited initial amounts of energy that is consumed in different rates depending on the power level and the intended receiver. We
An Experimental Comparison of MinCut/MaxFlow Algorithms for Energy Minimization in Vision
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2001
"... After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in lowlevel vision. The combinatorial optimization literature provides many mincut/maxflow algorithms with different polynomial time compl ..."
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Cited by 1315 (53 self)
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After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in lowlevel vision. The combinatorial optimization literature provides many mincut/maxflow algorithms with different polynomial time
What energy functions can be minimized via graph cuts?
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2004
"... In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such that the minimum cut on the graph also minimizes the energy. Yet, because these graph constructions are co ..."
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Cited by 1047 (23 self)
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In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such that the minimum cut on the graph also minimizes the energy. Yet, because these graph constructions
Results 1  10
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