The fractional Gaussian noise/fractional Brownian motion framework (fGn/fBm) has been widely used for modeling and interpreting physiological and behavioral data. The concept of 1/f noise, reflecting a kind of optimal...
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The fractional Gaussian noise/fractional Brownian motion framework (fGn/fBm) has been widely used for modeling and interpreting physiological and behavioral data. The concept of 1/f noise, reflecting a kind of optimal complexity in the underlying systems, is of central interest in this approach. It is generally considered that fGn and fBm represent a continuum, punctuated by the boundary of "ideal" 1/f noise. In the present paper, we focus on the correlation properties of discrete-time versions of these processes (dfGn and dfBm). We especially derive a new analytical expression of the autocorrelation function (ACF) of dfBm. We analyze the limit behavior of dfGn and dfBm when they approach their upper and lower limits, respectively. We show that, as H approaches 1, the ACF of dfGn tends towards 1 at all lags, suggesting that dfGn series tend towards straight line. Conversely, as H approaches 0, the ACF of dfBm tends towards 0 at all lags, suggesting that dfBm series tend towards white noise. These results reveal a severe breakdown of correlation properties around the 1/f boundary and challenge the idea of a smooth transition between dfGn and dfBm processes. We discuss the implications of these findings for the application of the dfGn/dfBm model to experimental series, in terms of theoretical interpretation and modeling.
This article presents a scalable mechanism for peer-to-peer (P2P) energy trading among prosumers in a smart grid. In the proposed mechanism, prosumers engage in a non-mediated negotiation with their peers to reach an ...
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This article presents a scalable mechanism for peer-to-peer (P2P) energy trading among prosumers in a smart grid. In the proposed mechanism, prosumers engage in a non-mediated negotiation with their peers to reach an agreement on the price and quantity of energy to be exchanged. Instead of concurrent bilateral negotiation between all peers with high overheads, an iterative peer matching process is employed to match peers for bilateral negotiation. The proposed negotiation algorithm enables prosumers to come to an agreement, given that they have no prior knowledge about the preference structure of their trading partners. A greediness factor is introduced to model the selfish behavior of prosumers in the negotiation process and to investigate its impact on the negotiation outcome. In order to recover the costs related to power losses, a transaction fee is applied to each transaction that enables the grid operator to recover incurred losses due to P2P trades. The case studies demonstrate that the proposed mechanism discourages greedy behavior of prosumers in the negotiation process as it does not increase their economic surplus. Also, it has an appropriate performance from the computation overheads and scalability perspectives.
This paper studies a scheduling problem with step-deteriorating jobs and multiple critical dates in a single machine environment, where each job's processing time increases stepwise at each critical date as its st...
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This paper studies a scheduling problem with step-deteriorating jobs and multiple critical dates in a single machine environment, where each job's processing time increases stepwise at each critical date as its start time is delayed. Our goal is to minimize the total weighted completion time. First, we prove that the problem is NP-hard when there is one critical date and that even the unweighted case with two critical dates remains NP-hard and has inapproximability. We further establish the strong NP-hardness for the unweighted case with an arbitrary number of critical dates. As solution approaches, we develop a mixed integer linear programming formulation and develop a heuristic based on the weighted shortest processing time rule. Finally, extensive numerical experiments were designed according to the level of difficulty in evaluating the performance of the proposed heuristic.
This paper presents a time-frequency-domain filtered-x LMS (FXLMS) algorithm for active noise control (ANC) based on the short-time Fourier transform (STFT). We show that proposed algorithm has much reduced computatio...
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This paper presents a time-frequency-domain filtered-x LMS (FXLMS) algorithm for active noise control (ANC) based on the short-time Fourier transform (STFT). We show that proposed algorithm has much reduced computational complexity and better convergence performance, as compared with the time-domain FXLMS algorithm. Additionally, computer simulations show that a time-frequency-domain FXLMS algorithm for ANC is effective in canceling non-stationary noise while a frequency-domain FXLMS algorithm remains inadequate at this task. (c) 2012 Elsevier Ltd. All rights reserved.
In this paper, we study the computational complexity and approximation complexity of the connected set-cover problem. We derive necessary and sufficient conditions for the connected set-cover problem to have a polynom...
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In this paper, we study the computational complexity and approximation complexity of the connected set-cover problem. We derive necessary and sufficient conditions for the connected set-cover problem to have a polynomial-time algorithm. We also present a sufficient condition for the existence of a (1 + ln delta)-approximation. In addition, one such (1 + ln delta)-approximation algorithm for this problem is proposed. Furthermore, it is proved that there is no polynomial-time -approximation for any for the connected set-cover problem on general graphs, unless NP has an quasi-polynomial Las-Vegas algorithm.
We take a fresh look at CD complexity, where CDt (x) is the size of the smallest program that distinguishes x from all other strings in time t (\x\). We also look at CND complexity, a new nondeterministic variant of C...
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We take a fresh look at CD complexity, where CDt (x) is the size of the smallest program that distinguishes x from all other strings in time t (\x\). We also look at CND complexity, a new nondeterministic variant of CD complexity, and time-bounded Kolmogorov complexity, denoted by C complexity. We show several results relating time-bounded C, CD, and CND complexity and their applications to a variety of questions in computational complexity theory, including the following: Showing how to approximate the size of a set using CD complexity without using the random string as needed in Sipser's earlier proof of a similar result. Also, we give a new simpler proof of this result of Sipser's. Improving these bounds for almost all strings, using extractors. A proof of the Valiant-Vazirani lemma directly from Sipser's earlier CD lemma. A relativized lower bound for CND complexity. Exact characterizations of equivalences between C, CD, and CND complexity. Showing that satisfying assignments of a satisfiable Boolean formula can be enumerated in time polynomial in the size of the output if and only if a unique assignment can be found quickly. This answers an open question of Papadimitriou. A new Kolmogorov complexity-based proof that BPP subset of or equal to Sigma(2)(p). New Kolmogorov complexity based constructions of the following relativized worlds: There exists an infinite set in with no sparse infinite NP subsets. EX = NEXP but there exists a NEXP machine whose accepting paths cannot be found in exponential time. Satisfying assignments cannot be found with nonadaptive queries to SAT.
Statistical quality of service (QoS) provisioning is a performance metric that determine the user satisfaction as the main purpose of future wireless networks. Effective capacity (EC) is a valuable quantity which help...
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Statistical quality of service (QoS) provisioning is a performance metric that determine the user satisfaction as the main purpose of future wireless networks. Effective capacity (EC) is a valuable quantity which helps analysing delay QoS performance as the most popular QoS metric. In this study, the authors concentrate on characterising the delay QoS performance via the EC of uplink transmission mode of individual users in multiuser centralised networks in which the user's transmitted signals may interfere with each other. To reduce the computational complexity of finding EC, the authors first propose closed form expressions for the EC of each user, with or without considering the inter-symbol interference (ISI). Then, two general algorithms are presented to clarify the relation of EC and QoS guarantee performance of a system in which the way of analysing QoS guarantee performance is explained step-by-step. By the use of these algorithms and the obtained closed form EC functions, the authors investigate the statistical delay QoS performance of individual users and the effects of channel conditions and ISI on their performance. The numerical results validate our analytical outcomes in deriving closed form equations and evaluate the offered schemes in characterising delay QoS performance.
作者：
Hladik, MilanCerny, MichalRada, MiroslavCharles Univ Prague
Fac Math & Phys Dept Appl Math Malostranske Nam 25 Prague 11800 Czech Republic Univ Econ
Fac Informat & Stat Dept Econometr W Churchills Sq 4 Prague 13067 Czech Republic Univ Econ
Fac Finance & Accounting Dept Financial Accounting & Auditing W Churchills Sq 4 Prague 13067 Czech Republic
We consider the quadratic optimization problem max(x is an element of C) x(T)Qx + q(T)x, where C subset of R-n is a box and r := rank(Q) is assumed to be O(1) (i.e., fixed). We show that this case can be solved in pol...
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We consider the quadratic optimization problem max(x is an element of C) x(T)Qx + q(T)x, where C subset of R-n is a box and r := rank(Q) is assumed to be O(1) (i.e., fixed). We show that this case can be solved in polynomial time for an arbitrary Q and q. The idea is based on a reduction of the problem to enumeration of faces of a certain zonotope in dimension O(r). This paper generalizes previous results where Q had been assumed to be positive semidefinite and no linear term was allowed in the objective function. Positive definiteness was a strong restriction and it is now relaxed. Generally, the problem is NP-hard;this paper describes a new polynomially solvable class of instances, larger than those known previously.
Extensive ground surveys of forest resources are expensive, and remote sensing is commonly used to extend surveys to large areas for which no ground data are available to provide more accurate estimates for forest man...
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Extensive ground surveys of forest resources are expensive, and remote sensing is commonly used to extend surveys to large areas for which no ground data are available to provide more accurate estimates for forest management decisions. Remote-sensing data for tree type classification are usually analysed at the individual tree level (object-based). However, due to computational challenges, most object-based studies cover only smaller areas and experience of larger areas is lacking. We present an approach for an object-based, unsupervised classification of trees into broadleaf or conifer using airborne light detection and ranging (lidar) data and colour infrared (CIR) images on a countrywide scale. We adjusted the classification procedure using field data from countrywide tree species trial (TST) plots, and verified it on data from the National Forest Inventory (NFI). Results of the object-based classification of the TST plots showed an overall accuracy of 84% and a kappa coefficient () of 0.61 when using all plots, and 92% and 0.79, respectively, when leaving out plots with larch. NFI plots were assigned to conifer- or broadleaf-dominated or mixed depending on the area covered by the segments of the two tree types. In areas where lidar data were collected specifically during leaf-off conditions, 71% of the NFI plots were assigned correctly into the three categories with =0.53. Using only NFI plots dominated by one type (broadleaf or conifer), 78% were categorized correctly with =0.61. These results demonstrate that using wall-to-wall remote-sensing data, unsupervised classification of forest stands into broadleaf, conifer, or mixed is possible with an accuracy comparable to that of limited area studies. However, challenges and restrictions of using countrywide airborne remote sensing data lie in the costs associated with data collection and the data processing time.
The moving least-squares (MLS) direct collocation meshless method (DCM) is an effective numerical scheme for solving the radiative heat transfer in participating media. In this method the trial function is constructed...
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The moving least-squares (MLS) direct collocation meshless method (DCM) is an effective numerical scheme for solving the radiative heat transfer in participating media. In this method the trial function is constructed by a MLS approximation and the radiative transfer equation (RTE) is discretized directly at nodes by collocation. The main drawback of this method is that, like most of the other numerical methods, the solution to the RTE by the DCM also suffers much from nonphysical oscillations in some cases caused by the convection-dominated property of the RTE. To overcome the numerical oscillations, special stabilization techniques are usually adopted, which increases the complexity and computation time of problem. In the present work a new scheme based on the outflow-boundary intensity interpolation correction is proposed that can easily ensure a large reduction in numerical oscillations of results without any complex stabilization technique. Adaptive support domain technique is also adopted, and the size of the support domain of each evaluated point changes with the density of nodes with irregular distribution. Five cases are studied to illustrate the numerical performance of these improvements. The numerical results compare well with the benchmark approximate solutions, and it is shown that the improved moving least-square direct collocation meshless method (iDCM) is easily implemented, efficient, of high accuracy, and excellent stability, to solve radiative heat transfer in homogeneous participating media.
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