Search results for "Numbers"
showing 10 items of 128 documents
Secure random number generation in wireless sensor networks
2011
The increasing adoption of wireless sensor networks as a flexible and inexpensive tool for the most diverseapplications, ranging from environmental monitoring to home automation, has raised more and more atten-tion to the issues related to the design of specifically customized security mechanisms. The scarcity ofcomputational, storage, and bandwidth resources cannot definitely be disregarded in such context, and thismakes the implementation of security algorithms particularly challenging. This paper proposes a securityframework for the generation of true random numbers, which are paramount as the core building blockfor many security algorithms; the intrinsic nature of wireless sensor nodes …
Can the Adaptive Metropolis Algorithm Collapse Without the Covariance Lower Bound?
2011
The Adaptive Metropolis (AM) algorithm is based on the symmetric random-walk Metropolis algorithm. The proposal distribution has the following time-dependent covariance matrix at step $n+1$ \[ S_n = Cov(X_1,...,X_n) + \epsilon I, \] that is, the sample covariance matrix of the history of the chain plus a (small) constant $\epsilon>0$ multiple of the identity matrix $I$. The lower bound on the eigenvalues of $S_n$ induced by the factor $\epsilon I$ is theoretically convenient, but practically cumbersome, as a good value for the parameter $\epsilon$ may not always be easy to choose. This article considers variants of the AM algorithm that do not explicitly bound the eigenvalues of $S_n$ away …
Estimating the geometric median in Hilbert spaces with stochastic gradient algorithms: Lp and almost sure rates of convergence
2016
The geometric median, also called L 1 -median, is often used in robust statistics. Moreover, it is more and more usual to deal with large samples taking values in high dimensional spaces. In this context, a fast recursive estimator has been introduced by Cardot et?al. (2013). This work aims at studying more precisely the asymptotic behavior of the estimators of the geometric median based on such non linear stochastic gradient algorithms. The L p rates of convergence as well as almost sure rates of convergence of these estimators are derived in general separable Hilbert spaces. Moreover, the optimal rates of convergence in quadratic mean of the averaged algorithm are also given.
An Adaptive Parallel Tempering Algorithm
2013
Parallel tempering is a generic Markov chainMonteCarlo samplingmethod which allows good mixing with multimodal target distributions, where conventionalMetropolis- Hastings algorithms often fail. The mixing properties of the sampler depend strongly on the choice of tuning parameters, such as the temperature schedule and the proposal distribution used for local exploration. We propose an adaptive algorithm with fixed number of temperatures which tunes both the temperature schedule and the parameters of the random-walk Metropolis kernel automatically. We prove the convergence of the adaptation and a strong law of large numbers for the algorithm under general conditions. We also prove as a side…
On the stability and ergodicity of adaptive scaling Metropolis algorithms
2011
The stability and ergodicity properties of two adaptive random walk Metropolis algorithms are considered. The both algorithms adjust the scaling of the proposal distribution continuously based on the observed acceptance probability. Unlike the previously proposed forms of the algorithms, the adapted scaling parameter is not constrained within a predefined compact interval. The first algorithm is based on scale adaptation only, while the second one incorporates also covariance adaptation. A strong law of large numbers is shown to hold assuming that the target density is smooth enough and has either compact support or super-exponentially decaying tails.
The coalescent in population models with time-inhomogeneous environment
2002
AbstractThe coalescent theory, well developed for the class of exchangeable population models with time-homogeneous reproduction law, is extended to a class of population models with time-inhomogeneous environment, where the population size is allowed to vary deterministically with time and where the distribution of the family sizes is allowed to change from generation to generation. A new class of time-inhomogeneous coalescent limit processes with simultaneous multiple mergers arises. Its distribution can be characterized in terms of product integrals.
Ridge-enhanced optical transmission through a continuous metal film
2004
Optical transmission through a continuous (without holes) metal film with a periodic structure of metal or dielectric ridges on one or both interfaces was numerically studied. The dependencies of the transmission on the ridge width and height as well as the ridge arrangements on the opposite interfaces were investigated in weak- and strong-coupling regimes. The transmission enhancement was shown to depend on the relative position of the ridge gratings on the opposite interfaces of a film, confirming the role of resonant tunneling processes involving states of the surface polariton Bloch modes.
Enseñanza de las ciencias : revista de investigación y experiencias didácticas
2020
Nuestro objetivo en esta investigación es identificar las dificultades de aprendizaje que tienen los niños de 1.º a 3.º grado de educación primaria en la construcción de los números naturales. Tales dificultades no proceden de la enseñanza, sino de las propias matemáticas y para poder observar esas dificultades, es necesario reducir el problema a los elementos primitivos. Con los modelos teóricos locales como marco teórico y metodológico, se ha diseñado un modelo de enseñanza traduciendo el componente formal (modelo de J. Von Neumann) a una secuencia de actividades con el uso de material manipulativo. Se analiza la experiencia de enseñanza y en los resultados se destacan y explican las difi…
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.
2019
Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …
On the classification of large residential buildings stocks by sample typologies for energy planning purposes
2014
Local and central administrations are often called to properly allocate economic resources intended for the territorial energy planning, on the basis of the performances achieved by implementing energy conservation measures. Particularly in the residential sector, that represents one of the most relevant sector for the energy demand, effective and reliable evaluation tools are required for this aim. Unfortunately, building stocks are characterized by a very large number of buildings that are referred to different construction periods and are equipped with a variety of appliances and tools, other than with different heating and cooling systems. This means that the whole energy consumption of…