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See detailOptimal control for rough differential equations
Mazliak, Laurent; Nourdin, Ivan UL

in Stochastics and Dynamics (2008), 8(1), 23-33

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See detailAn Optimal Control Solution to the Constrained Weight Portfolio Optimisation Problem with Conditioning Information
Boissaux, Marc; Schiltz, Jang UL

Scientific Conference (2010, June 04)

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See detailOptimal Convergence Rates and One-Term Edgeworth Expansions for Multidimensional Functionals of Gaussian Fields
Campese, Simon UL

in ALEA: Latin American Journal of Probability and Mathematical Statistics (2013)

We develop techniques for determining the exact asymptotic speed of convergence in the multidimensional normal approximation of smooth functions of Gaussian fields. As a by-product, our findings yield ... [more ▼]

We develop techniques for determining the exact asymptotic speed of convergence in the multidimensional normal approximation of smooth functions of Gaussian fields. As a by-product, our findings yield exact limits and often give rise to one-term generalized Edgeworth expansions increasing the speed of convergence. Our main mathematical tools are Malliavin calculus, Stein's method and the Fourth Moment Theorem. This work can be seen as an extension of the results of arXiv:0803.0458 to the multi-dimensional case, with the notable difference that in our framework covariances are allowed to fluctuate. We apply our findings to exploding functionals of Brownian sheets, vectors of Toeplitz quadratic functionals and the Breuer-Major Theorem. [less ▲]

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See detailOptimal convergence rates for the invariant density estimation of jump-diffusion processes
Amorino, Chiara UL; Nualart, Eulalia

E-print/Working paper (2021)

We aim at estimating the invariant density associated to a stochastic differential equation with jumps in low dimension, which is for d = 1 and d = 2. We consider a class of jump diffusion processes whose ... [more ▼]

We aim at estimating the invariant density associated to a stochastic differential equation with jumps in low dimension, which is for d = 1 and d = 2. We consider a class of jump diffusion processes whose invariant density belongs to some Hölder space. Firstly, in dimension one, we show that the kernel density estimator achieves the convergence rate 1/T, which is the optimal rate in the absence of jumps. This improves the convergence rate obtained in [Amorino, Gloter (2021)], which depends on the Blumenthal-Getoor index for d = 1 and is equal to log T/T for d = 2. Secondly, we show that is not possible to find an estimator with faster rates of estimation. Indeed, we get some lower bounds with the same rates { 1/T , log T/T } in the mono and bi-dimensional cases, respectively. Finally, we obtain the asymptotic normality of the estimator in the one-dimensional case. [less ▲]

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See detailOptimal day-ahead trading and storage of renewable energies—an approximate dynamic programming approach
Löhndorf, Nils UL; Minner, Stefan

in Energy Systems (2010), 1(1), 61--77

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See detailOptimal Deployment of Base Stations in Cognitive Satellite Terrestrial Networks
Vuppala, Satyanarayana UL; Sellathurai, Mathini; Chatzinotas, Symeon UL

in 2018 9th Advanced Satellite Multimedia Systems Conference and the 15th Signal Processing for Space Communications Workshop (ASMS/SPSC) (2018)

The application of linear precoding at the gateway side enables broadband multibeam satellite systems to use more aggressive frequency reuse patterns increasing the overall capacity of future High ... [more ▼]

The application of linear precoding at the gateway side enables broadband multibeam satellite systems to use more aggressive frequency reuse patterns increasing the overall capacity of future High Throughput Satellites (HTS). However, although some previous works about precoding consider imperfect CSIT (Chanel State Information at the Transmitter) adding some CSI estimation errors, that is not the main cause of CSI degradation. In practice, receivers can only detect and estimate a few coefficients of the CSI vector being the other nullified, replaced by zeros. This introduces errors in the SINR calculation by the gateway that lead to the assignment of Modulation and Coding Schemes (MCS) over the decoding possibilities of the users, increasing the rate of erroneous frames. In this work, the errors in the SINR calculation caused by the nullification of the CSI are analyzing statistically and geographically using a radiation diagram of 245 beams over Europe. Furthermore, a solution based on a link adaptation algorithm with a per user adaptive margin is proposed, helping to achieve the QEF (Quasi-error Free) target of DVB-S2X systems. [less ▲]

Detailed reference viewed: 42 (0 UL)
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See detailOptimal Design of Ad Hoc Injection Networks by Using Genetic Algorithms
Danoy, Grégoire UL; Bouvry, Pascal UL; Brust, Matthias R. UL et al

in 9th annual conference on Genetic and evolutionary computation (GECCO '07) (2007)

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See detailOptimal design of cap screw thread runout for transversal and axial loads
Kedziora, Slawomir UL

in Journal of Applied Mechanical Engineering (2017), 6(1),

t The presented work is focused on a design of a new thread runout of screws and bolts subjected by transversal loads. These types of loads can occur in a normal service of bolt connection and they can ... [more ▼]

t The presented work is focused on a design of a new thread runout of screws and bolts subjected by transversal loads. These types of loads can occur in a normal service of bolt connection and they can lead to a failure. Two failure modes of the screw could occur: self-loosening of the screw or fatigue failure of the screw. The latter failure mode is analysed in the presented project focusing on an improvement of the existing design of the screws in terms of fatigue failure. The fatigue fracture of the screws, which are loaded by the transversal load, occurs normally in a groove of a first thread run of an engagement. A shape of the thread runout has some influence on stress in the thread therefore that shape can optimize to minimize the thread stress. Considering this, free shape optimisation was employed to find the best runout shape. As results of the presented work, the optimum design of the thread runout is proposed for the analysed conditions. The elaborated design of the cap screw brings significant improvement of the lifetime when the cycling tangential load occurs. In addition, the new design gives the better structural performance than the existing designs also for the cycling normal loads [less ▲]

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See detailOptimal design of fractional order linear system with stochastic inputs/parametric uncertainties by hybrid spectral method
Duong, Pham UL

in Journal of Process Control (2014), 24(10), 1639-1645

"t" "This paper reports the design of a fractional linear system under stochastic inputs/uncertainties. The" "design methods were based on the hybrid spectral method for expanding the system signals over ... [more ▼]

"t" "This paper reports the design of a fractional linear system under stochastic inputs/uncertainties. The" "design methods were based on the hybrid spectral method for expanding the system signals over ortho- gonal functions. The use of the hybrid spectral method led to algebraic relationships between the first and second order stochastic moments of the input and output of a system. The spectral method could obtain a highly accurate solution with less computational demand than the traditional Monte Carlo method. Based on the hybrid spectral framework, the optimal design was elaborated by minimizing the suitably" "defined constrained-optimization problem." [less ▲]

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See detailOptimal design of stochastic distributed order linear SISO systems using hybrid spectral method
Duong, Pham UL

in Mathematical Problems in Engineering (2015), 2015

The distributed order concept, which is a parallel connection of fractional order integrals and derivatives taken to the infinitesimal limit in delta order, has been the main focus in many engineering ... [more ▼]

The distributed order concept, which is a parallel connection of fractional order integrals and derivatives taken to the infinitesimal limit in delta order, has been the main focus in many engineering areas recently. On the other hand, there are few numerical methods available for analyzing distributed order systems, particularly under stochastic forcing. This paper proposes a novel numerical scheme for analyzing the behavior of a distributed order linear single input single output control system under random forcing. The method is based on the operational matrix technique to handle stochastic distributed order systems. The existing Monte Carlo, polynomial chaos, and frequency methods were first adapted to the stochastic distributed order system for comparison. Numerical examples were used to illustrate the accuracy and computational efficiency of the proposed method for the analysis of stochastic distributed order systems. The stability of the systems under stochastic perturbations can also be inferred easily from the moment of random output obtained using the proposed method. Based on the hybrid spectral framework, the optimal design was elaborated on by minimizing the suitably defined constrained-optimization problem. [less ▲]

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See detailOptimal Detection of Multiple Symbol-Slotted Random Access based Packet Transmissions
Kisseleff, Steven UL; Gerstacker, Wolfgang H.

in IEEE Wireless Communications Letters (2021)

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See detailOptimal dispatching of electric and hybrid buses subject to scheduling and charging constraints
Rinaldi, Marco UL; Parisi, Federico; Laskaris, Georgios UL et al

Scientific Conference (2018, November)

We consider the problem of optimally determining the sequence of electric and hybrid buses departing from a multi-line bus terminal, considering both service constraints (schedule adherence) and energy ... [more ▼]

We consider the problem of optimally determining the sequence of electric and hybrid buses departing from a multi-line bus terminal, considering both service constraints (schedule adherence) and energy constraints (electric bus charging status, bus recharging scheduling in capacitated facilities). The problem is formulated as a Mixed Integer Linear Program, with the objective of minimizing the total operational cost for the bus lines in question. System dynamics are captured by practical sets of constraints, ranging from scheduling adherence to discharge- recharge dynamics. Individual operational costs at the bus level and at the trip level are fully parametrized, allowing for extensive sensitivity analysis. We investigate a real-life case study based on the city of Luxembourg, where two charging stations have been installed in the central station’s bus terminal. Experimental results show that, while full electrification is indeed possible, the required fleet size depends strongly on the given line(s) timetable. [less ▲]

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See detailOptimal Employment Subsidies and Market Structures in Industries with Unemployment
Picard, Pierre M UL

in Oxford Economic Papers (2001), 53(2), 352-372

In this paper we analyze the issue of optimal employment subsidies in imperfectly competitive industries in which a distortion in the labour market generates involuntary unemployment. As a benchmark case ... [more ▼]

In this paper we analyze the issue of optimal employment subsidies in imperfectly competitive industries in which a distortion in the labour market generates involuntary unemployment. As a benchmark case, we focus on monopolies and duopolies and on complete information between firms and government. We characterize the levels and creations of employment in the subsidized industry and we check when such employment policies are more favorable to the least productive firms. [less ▲]

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See detailOptimal Employment Subsidies to Heterogeneous Workers: Unemployment-Trap, Job-Additionality and Tax Rates
Picard, Pierre M UL

in Annales d’Economie et de Statistique = Annals of Economics and Statistics (2001), 62

Unemployment and welfare benefits generate unemployment traps. In this paper, we design the optimal employment subsidies that allow governments to reduce unemployment traps under constant budget deficit ... [more ▼]

Unemployment and welfare benefits generate unemployment traps. In this paper, we design the optimal employment subsidies that allow governments to reduce unemployment traps under constant budget deficit and without diminishing workers' welfare. We explore the effects of work incentives on the shape and on the properties of employment subsidies. We finally address the issues of self-help effect and job-additionality. [less ▲]

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See detailOptimal equilibrium stabilization for a nonlinear infinite-dimensional plug-flow reactor model
Hastir, Anthony; Lamoline, François UL

in Automatica (2021), 130

This paper studies the stabilization of optimal equilibrium profiles in nonisothermal plug-flow tubular reactors actuated by a heat exchanger that acts as a distributed control input. As a first result ... [more ▼]

This paper studies the stabilization of optimal equilibrium profiles in nonisothermal plug-flow tubular reactors actuated by a heat exchanger that acts as a distributed control input. As a first result, we show that the heat exchanger temperature that achieves the minimal value of the steady-state reactant concentration at the outlet is the maximal allowed one. Then, a control strategy is proposed to reach these optimal equilibrium profiles. As main results, we prove that the control law stabilizes exponentially the nonlinear dynamics around the optimal equilibrium while it converges to the optimal heat exchanger temperature. In addition we show that the control law is optimal for some cost criterion of infinite-horizon integral type. Finally, the main results are illustrated with some numerical simulations. [less ▲]

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See detailOptimal First-Order Boolean Masking for Embedded IoT Devices
Biryukov, Alex UL; Dinu, Dumitru-Daniel UL; Le Corre, Yann UL et al

in CARDIS 2017: Smart Card Research and Advanced Applications (2018, January 26)

Boolean masking is an effective side-channel countermeasure that consists in splitting each sensitive variable into two or more shares which are carefully manipulated to avoid leakage of the sensitive ... [more ▼]

Boolean masking is an effective side-channel countermeasure that consists in splitting each sensitive variable into two or more shares which are carefully manipulated to avoid leakage of the sensitive variable. The best known expressions for Boolean masking of bitwise operations are relatively compact, but even a small improvement of these expressions can significantly reduce the performance penalty of more complex masked operations such as modular addition on Boolean shares or of masked ciphers. In this paper, we present and evaluate new secure expressions for performing bitwise operations on Boolean shares. To this end, we describe an algorithm for efficient search of expressions that have an optimal cost in number of elementary operations. We show that bitwise AND and OR on Boolean shares can be performed using less instructions than the best known expressions. More importantly, our expressions do no require additional random values as the best known expressions do. We apply our new expressions to the masked addition/subtraction on Boolean shares based on the Kogge-Stone adder and we report an improvement of the execution time between 14% and 19%. Then, we compare the efficiency of first-order masked implementations of three lightweight block ciphers on an ARM Cortex-M3 to determine which design strategies are most suitable for efficient masking. All our masked implementations passed the t-test evaluation and thus are deemed secure against first-order side-channel attacks. [less ▲]

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See detailThe optimal fourth moment theorem
Nourdin, Ivan UL; Peccati, Giovanni UL

in Proceedings of the American Mathematical Society (2015), 143(7), 3123-3133

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See detailOptimal fractional linear prediction with restricted memory
Skovranek, Tomas; Despotovic, Vladimir UL; Peric, Zoran

in IEEE Signal Processing Letters (2019), 26(5), 760-764

Linear prediction is extensively used in modeling, compression, coding, and generation of speech signal. Various formulations of linear prediction are available, both in time and frequency domain, which ... [more ▼]

Linear prediction is extensively used in modeling, compression, coding, and generation of speech signal. Various formulations of linear prediction are available, both in time and frequency domain, which start from different assumptions but result in the same solution. In this letter, we propose a novel, generalized formulation of the optimal low-order linear prediction using the fractional (non-integer) derivatives. The proposed fractional derivative formulation allows for the definition of predictor with versatile behavior based on the order of fractional derivative. We derive the closed-form expressions of the optimal fractional linear predictor with restricted memory, and prove that the optimal first-order and the optimal second-order linear predictors are only its special cases. Furthermore, we empirically prove that the optimal order of fractional derivative can be approximated by the inverse of the predictor memory, and thus, it is a priori known. Therefore, the complexity is reduced by optimizing and transferring only one predictor coefficient, i.e., one parameter less in comparison to the second-order linear predictor, at the same level of performance. [less ▲]

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See detailOptimal Growth and Uncertainty: Learning
Koulovatianos, Christos UL; Mirman, Leonard; Santugini, Marc

in Journal of Economic Theory (2009), 144

We introduce learning in a Brock-Mirman environment and study the effect of risk generated by the planner’s econometric activity on optimal consumption and investment. Here, learning introduces two ... [more ▼]

We introduce learning in a Brock-Mirman environment and study the effect of risk generated by the planner’s econometric activity on optimal consumption and investment. Here, learning introduces two sources of risk about future payoffs: structural uncertainty and uncertainty from the anticipation of learning. The latter renders control and learning nonseparable. We present two sets of results in a learning environment. First, conditions under which the introduction of learning increases or decreases optimal consumption are provided. The effect depends on the strengths and directions of the two sources of risk, which may pull in opposite directions. Second, the effects of changes in the mean and riskiness of the distribution of the signal and initial beliefs on optimal consumption are studied. [less ▲]

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See detailOptimal hard fusion strategies for cognitive radio networks
Maleki, Sina UL; Prabhakar Chepuri, Sundeep; Leus, Geert

in IEEE Wireless Communications and Networking Conference (WCNC), 2011 (2011, March)

Optimization of hard fusion spectrum sensing using the k-out-of-N rule is considered. Two different setups are used to derive the optimal k. A throughput optimization setup is defined by minimizing the ... [more ▼]

Optimization of hard fusion spectrum sensing using the k-out-of-N rule is considered. Two different setups are used to derive the optimal k. A throughput optimization setup is defined by minimizing the probability of false alarm subject to a probability of detection constraint representing the interference of a cognitive radio with the primary user, and an interference management setup is considered by maximizing the probability of detection subject to a false alarm rate constraint. It is shown that the underlying problems can be simplified to equality constrained optimization problems and an algorithm to solve them is presented. We show the throughput optimization and interference management setups are dual. The simulation results show the majority rule is optimal or near optimal for the desirable range of false alarm and detection rates for a cognitive radio network. Furthermore, an energy efficient setup is considered where the number of cognitive radios is to be minimized for the AND and the OR rule and a certain probability of detection and false alarm constraint. The simulation results show that the OR rule outperforms the AND rule in terms of energy efficiency. [less ▲]

Detailed reference viewed: 119 (0 UL)