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A Modified StepLength Algorithm In Nonlinear A Modified StepLength Algorithm In Nonlinear Programming Programming
"... : Abstract: In this paper we consider a modification of the Armijo steplength algorithm based on socalled "forcing functions". It is proved that this modified algorithm is welldefined. Proof is given of the convergence of the obtained sequence of points to a firstorder point of the probl ..."
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: Abstract: In this paper we consider a modification of the Armijo steplength algorithm based on socalled "forcing functions". It is proved that this modified algorithm is welldefined. Proof is given of the convergence of the obtained sequence of points to a firstorder point
Maximin Algorithm With a StepLength Estimation Technique
"... Abstract—We propose a technique that enhances the performance of Torrieri and Bakhru’s maximin algorithm in the presence of frequency offsets and modulated interferences, a common scenario in multipleaccess environments, where we observed that the Maximin algorithm suffers performance degradation ..."
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degradation in the aforesaid scenario. To combat modulated interferences and fading effects, we propose to update the step length during every smart antenna weight vector update. We found that our scheme improves the robustness of the maximin algorithm to a greater extent. Simulation results for a frequency
PerformanceEffective and LowComplexity Task Scheduling for Heterogeneous Computing
 IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
, 2002
"... Efficient application scheduling is critical for achieving high performance in heterogeneous computing environments. The application scheduling problem has been shown to be NPcomplete in general cases as well as in several restricted cases. Because of its key importance, this problem has been exte ..."
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Cited by 255 (0 self)
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and the CriticalPathonaProcessor (CPOP) algorithm. The HEFT algorithm selects the task with the highest upward rank value at each step and assigns the selected task to the processor, which minimizes its earliest finish time with an insertionbased approach. On the other hand, the CPOP algorithm uses
Nonlinear System Modelling Using Output Error Estimation Of A Local Model Network
, 1996
"... The local model network is a set of models, each describing the same dynamic system but at different operating points. The outputs of these local models are weighted according to the current operating point and summed to give the local model network output. A local model network can be constructed f ..."
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Cited by 3 (1 self)
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parameters. This network can be simulated using a variable step length algorithm in a format amenable to a standard simulation program. An example is given in which the flow in a coupled tank system is analysed. INTRODUCTION It is often the case that one physical model cannot represent the complete
HighPerformance Algorithms for Drift Avoidance and Fast Tracking in Solar MPPT System
"... Abstract—The power available at the output of solar arrays keeps changing with solar insolation and ambient temperature. Expensive and inefficient, the solar arrays must be operated at maximum power point (MPP) continuously for economic reasons. Of the numerous algorithms for this purpose, perturb a ..."
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. With continually changing atmospheric conditions, these inadequacies lead to poor utilization of solar arrays. This paper addresses both the issues. A variablesteplength algorithm is proposed to eliminate the tradeoff. The drift is minimized by evaluating the entire trend in a power versus voltage curve
WiBEST: A Hybrid Personal Indoor Positioning System
"... Environmental Sensor Tracking platform, for personal indoor positioning. WiBEST is built with portable onbody sensor nodes and assisted sensor nodes deployed in the targeted indoor area. It takes a hybrid approach with pedestrian dead reckoning and radiobased localization and explore the their coo ..."
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the their cooperative efforts. Realtime inertial measurements are combined with RSSIbased information, and then processed with an Extended Kalman Filter to be weighted in the location estimation according to their reliability. WiBEST also incorporates with an adaptive Step Length Algorithm to reduce the deviation
Bayesian inference on phylogeny and its impact on evolutionary biology.
 Science
, 2001
"... 1 As a discipline, phylogenetics is becoming transformed by a flood of molecular data. These data allow broad questions to be asked about the history of life, but also present difficult statistical and computational problems. Bayesian inference of phylogeny brings a new perspective to a number of o ..."
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Cited by 235 (10 self)
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distribution that is the posterior probability distribution of the parameters. For the phylogeny problem, the MCMC algorithm involves two steps: (i) A new tree is proposed by stochastically perturbing the current tree. (ii) This tree is then either accepted or rejected with a probability described
The PATH Solver: A NonMonotone Stabilization Scheme for Mixed Complementarity Problems
 OPTIMIZATION METHODS AND SOFTWARE
, 1995
"... The Path solver is an implementation of a stabilized Newton method for the solution of the Mixed Complementarity Problem. The stabilization scheme employs a pathgeneration procedure which is used to construct a piecewiselinear path from the current point to the Newton point; a step length acceptan ..."
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Cited by 213 (40 self)
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The Path solver is an implementation of a stabilized Newton method for the solution of the Mixed Complementarity Problem. The stabilization scheme employs a pathgeneration procedure which is used to construct a piecewiselinear path from the current point to the Newton point; a step length
Step Length Adaptation on Ridge Functions
, 2006
"... Step length adaptation is central to evolutionary algorithms in realvalued search spaces. This paper contrasts several step length adaptation algorithms for evolution strategies on a family of ridge functions. The algorithms considered are cumulative step length adaptation, a variant of mutative se ..."
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Cited by 6 (0 self)
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Step length adaptation is central to evolutionary algorithms in realvalued search spaces. This paper contrasts several step length adaptation algorithms for evolution strategies on a family of ridge functions. The algorithms considered are cumulative step length adaptation, a variant of mutative
Layered Representation of Motion Video using Robust MaximumLikelihood Estimation of Mixture Models and MDL Encoding
, 1995
"... Representing and modeling the motion and spatial support of multiple objects and surfaces from motion video sequences is an important intermediate step towards dynamic image understanding. One such representation, called layered representation, has recently been proposed. Although a number of algori ..."
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Cited by 204 (4 self)
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of algorithms have been developed for computing these representations, there has not been a consolidated effort into developing a precise mathematical formulation of the problem. This paper presents such a formulation based on maximum likelihood estimation of mixture models and the minimum description length
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