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Processor Speed Control with Thermal Constraints
Convex optimization distributed control primal-dual interior-point methods
2015/7/9
We consider the problem of adjusting speeds of multiple computer processors sharing the same thermal environment, such as a chip or multi-chip package. We assume that the speed of processor (and assoc...
Receding Horizon Control: Automatic Generation of High-Speed Solvers
Receding Horizon Control Automatic Generation High-Speed Solvers
2015/7/9
Receding horizon control (RHC), also known as model predictive control (MPC), is a general purpose control scheme that involves repeatedly solving a constrained optimization problem, using predictions...
Minimum-Time Speed Optimization Along a Fixed Path
minimum-time trajectory generation optimal speed control convex optimisation
2015/7/9
In this paper we investigate the problem of optimizing the speed of a vehicle over a fixed path for minimum time traversal. We utilize a change of variables that has been known since the 1980s, althou...
High-speed kinks in a generalized discrete phi(4) model
The generalized discrete model moving kink
2014/12/25
We consider a generalized discrete ϕ4 model and demonstrate that it can support exact moving kink solutions in the form of tanh with an arbitrarily large velocity. The constructed exact moving so...
In this note the relation between the range-renewal speed and entropy for i.i.d. models is discussed.
Comparison of nonhomogeneous regression models for probabilistic wind speed forecasting
Comparison nonhomogeneous regression models probabilistic wind speed forecasting
2013/6/14
In weather forecasting, nonhomogeneous regression is used to statistically postprocess forecast ensembles in order to obtain calibrated predictive distributions. For wind speed forecasts, the regressi...
Probabilistic wind speed forecasting using Bayesian model averaging with truncated normal components
Bayesian model averaging continuous ranked probability score ensemble calibration truncated normal distribution
2013/6/13
Bayesian model averaging (BMA) is a statistical method for post-processing forecast ensembles of atmospheric variables, obtained from multiple runs of numerical weather prediction models, in order to ...
In many recent applications, data is plentiful. By now, we have a rather clear understanding of how more data can be used to improve the accuracy of learning algorithms. Recently, there has been a gro...
On the Speed of the One-dimensional Excited Random Walk in the Transient Regime
Excited Random Walk Pertubed Random Walk Law of Large Numbers
2009/6/12
We study a class of nearest-neighbor discrete time integer random walks introduced by Zerner (2005), the so called multi-excited random walks. The jump probabilities for such random walker have a drif...