A prototype problem in hypotheses testing is discussed. The problem of deciding whether an i.i.d. sequence of random variables has originated from a known source P1 or an unknown source P2 is considered. The exponential rate of decrease in type II probability of error under a constraint on the minimal rate of decrease in type I probability of error is chosen for a criterion of optimality. Using large deviations estimates, a decision rule that is based on the relative entropy of the empirical measure with respect to P1 is proposed. In the case of discrete random variables, this approach yields weaker results than the combinatorial approach used by Hoeffding (1965). However, it enables the analysis to be extended to the general case of Rn-valued random variables. Finally, the results are extended to the case where P1 is an unknown parameter-dependent distribution that is known to belong to a set of distributions (P01, &thetas;∈Θ) 相似文献
Indexing moving objects (MO) is a hot topic in the field of moving objects databases since many years. An impressive number
of access methods have been proposed to optimize the processing of MO-related queries. Several methods have focused on spatio-temporal
range queries, which represent the foundation of MO trajectory queries. Surprisingly, only a few of them consider that the
objects movements are constrained. This is an important aspect for several reasons ranging from better capturing the relationship
between the trajectory and the network space to more accurate trajectory representation with lower storage requirements. In
this paper, we propose T-PARINET, an access method to efficiently retrieve the trajectories of objects moving in networks.
T-PARINET is designed for continuous indexing of trajectory data flows. The cornerstone of T-PARINET is PARINET, an efficient
index for historical trajectory data. The structure of PARINET is based on a combination of graph partitioning and a set of
composite B+-tree local indexes. Because the network can be modeled using graphs, the partitioning of the trajectory data makes use of
graph partitioning theory and can be tuned for a given query load and a given data distribution in the network space. The
tuning process is built on a good quality cost model that is supplied with PARINET. The advantage of having a cost model is
twofold; it allows a better integration of the index into the query optimizer of any DBMS, and it permits tuning the index
structure for better performance. The tuning process can be performed before the index creation in the case of historical
data or online in the case of indexing data flows. In fact, massive online updates can degrade the index quality, which can
be measured by the cost model. We propose a specific maintenance process that results into T-PARINET. We study different types
of queries and provide an optimized configuration for several scenarios. T-PARINET can easily be integrated into any RDBMS,
which is an essential asset particularly for industrial or commercial applications. The experimental evaluation under an off-the-shelf
DBMS shows that our method is robust. It also significantly outperforms the reference R-tree-based access methods for in-network
trajectory databases. 相似文献
Preserving cultural heritage is one of the most intricate jobs that need to be performed with a lot of caution. Transporting artworks on the other hand, i.e., getting them out of their home museums and exposing them in uncontrollable and dynamic environments, makes preservation even harder. So far, museums try to contend against the dynamic context during transportation by employing high-class transport cases. However, no attempts are made to exploit the science of data. In this paper, we make use of the ubiquity of sensors and IoT devices, combined with advanced predictive analytics in order to manage processes based on their context and to anticipate challenging run-time violations. Our approach is tested on real datasets and transport scenarios to prove its efficiency.
Consider the one-dimensional filtering problem with state diffusion coefficient γ and observation noise coefficient 1−γ, where
is fixed. In the regime →0, we provide an example of state dynamics and a corresponding asymptotically optimal filter whose memory length is short in a strong sense. This stands in contrast with the behavior of the correlation memory length, proposed in [7], which stays bounded away from zero as →0. 相似文献
The smoothing of diffusions dxt = f(xt) dt + σ(xt) dwt, measured by a noisy sensor dyt = h(xt) dt + dvt, where wt and vt are independent Wiener processes, is considered in this paper. By focussing our attention on the joint p.d.f. of (xτxt), 0 ≤ τ < t, conditioned on the observation path {ys, 0 ≤ s ≤ t}, the smoothing problem is represented as a solution of an appropriate joint filtering problem of the process, together with its random initial conditions. The filtering problem thus obtained possesses a solution represented by a Zakai-type forward equation. This solution of the smoothing problem differs from the common approach where, by concentrating on the conditional p.d.f. of xτ alone, a set of ‘forward and reverse’ equations needs to be solved. 相似文献
As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification.For this purpose,a novel model-independent nonsingular terminal slidingmode control(MINTSMC)using the basic principles of the ultralocal model(ULM)and combined with the single input interval type-2 fuzzy logic control(SIT2-FLC)is developed for non-linear wind turbine pitch angle control.In the suggested control framework,the MINTSMC scheme is designed to regulate the wind turbine speed rotor,and a sliding-mode(SM)observer is adopted to estimate the unknown phenomena of the ULM.The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error.Extensive examinations and comparative analyses were made using a real-time softwarein-the-loop(RT-SiL)based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested modelindependent scheme in a real-time testbed. 相似文献
We apply the theory of products of random matrices to the analysis of multi-user communication channels similar to the Wyner model, which are characterized by short-range intra-cell broadcasting. We study fluctuations of the per-cell sum-rate capacity in the non-ergodic regime and provide results of the type of the central limit theorem (CLT) and large deviations (LD). Our results show that CLT fluctuations of the per-cell sum-rate Cm are of order \(1/\sqrt m \), where m is the number of cells, whereas they are of order 1/m in classical random matrix theory. We also show an LD regime of the form P(|Cm ? C| > ?) ≤ e?mα with α = α(?) > 0 and C = \(\mathop {\lim }\limits_{m \to \infty } \)Cm, as opposed to the rate \(e^{ - m^2 \alpha } \) in classical random matrix theory. 相似文献
The one-dimensional diffusion xt satisfying dxt = f(xt)dt + dwt, where wt is a standard Brownian motion and f(x) satisfies the Bene
condition f′(x) + f2(x) = ax2 + bx + c for all real x, is considered. It is shown that this diffusion does not admit a stationary probability measure except for the linear case f(x) = αx + β, α < 0. 相似文献
The problem of deciding whether a sample of a random field was generated by a Gaussian distribution is considered. Based on extensions of large deviation estimates due to M.D. Donsker and S.R.S. Varadhan (1985), a test that is optimal in a generalized Neyman-Pearson sense is proposed. This test turns out to depend on properties of the entropy of Gaussian processes and does not depend on cumulant computations 相似文献