802 resultados para Learning with noise


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We show that measurements of finite duration performed on an open two-state system can protect the initial state from a phase-noisy environment, provided the measured observable does not commute with the perturbing interaction. When the measured observable commutes with the environmental interaction, the finite-duration measurement accelerates the rate of decoherence induced by the phase noise. For the description of the measurement of an observable that is incompatible with the interaction between system and environment, we have found an approximate analytical expression, valid at zero temperature and weak coupling with the measuring device. We have tested the validity of the analytical predictions against an exact numerical approach, based on the superoperator-splitting method, that confirms the protection of the initial state of the system. When the coupling between the system and the measuring apparatus increases beyond the range of validity of the analytical approximation, the initial state is still protected by the finite-time measurement, according with the exact numerical calculations.

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Base-level maps (or ""isobase maps"", as originally defined by Filosofov, 1960), express a relationship between valley order and topography. The base-level map can be seen as a ""simplified"" version of the original topographic surface, from which the ""noise"" of the low-order stream erosion was removed. This method is able to identify areas with possible tectonic influence even within lithologically uniform domains. Base-level maps have been recently applied in semi-detail scale (e.g., 1:50 000 or larger) morphotectonic analysis. In this paper, we present an evaluation of the method's applicability in regional-scale analysis (e.g., 1:250 000 or smaller). A test area was selected in northern Brazil, at the lower course of the Araguaia and Tocantins rivers. The drainage network extracted from SRTM30_PLUS DEMs with spatial resolution of approximately 900 m was visually compared with available topographic maps and considered to be compatible with a 1:1,000 000 scale. Regarding the interpretation of regional-scale morphostructures, the map constructed with 2nd and 3rd-order valleys was considered to present the best results. Some of the interpreted base-level anomalies correspond to important shear zones and geological contacts present in the 1:5 000 000 Geological Map of South America. Others have no correspondence with mapped Precambrian structures and are considered to represent younger, probably neotectonic, features. A strong E-W orientation of the base-level lines over the inflexion of the Araguaia and Tocantins rivers, suggest a major drainage capture. A N-S topographic swath profile over the Tocantins and Araguaia rivers reveals a topographic pattern which, allied with seismic data showing a roughly N-S direction of extension in the area, lead us to interpret this lineament as an E-W, southward-dipping normal fault. There is also a good visual correspondence between the base-level lineaments and geophysical anomalies. A NW-SE lineament in the southeast of the study area partially corresponds to the northern border of the Mosquito lava field, of Jurassic age, and a NW-SE lineament traced in the northeastern sector of the study area can be interpreted as the Picos-Santa Ines lineament, identifiable in geophysical maps but with little expression in hypsometric or topographic maps.

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We consider binary infinite order stochastic chains perturbed by a random noise. This means that at each time step, the value assumed by the chain can be randomly and independently flipped with a small fixed probability. We show that the transition probabilities of the perturbed chain are uniformly close to the corresponding transition probabilities of the original chain. As a consequence, in the case of stochastic chains with unbounded but otherwise finite variable length memory, we show that it is possible to recover the context tree of the original chain, using a suitable version of the algorithm Context, provided that the noise is small enough.

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The aim of this Study was to compare the learning process of a highly complex ballet skill following demonstrations of point light and video models 16 participants divided into point light and video groups (ns = 8) performed 160 trials of a pirouette equally distributed in blocks of 20 trials alternating periods of demonstration and practice with a retention test a day later Measures of head and trunk oscillation coordination d1 parity from the model and movement time difference showed similarities between video and point light groups ballet experts evaluations indicated superiority of performance in the video over the point light group Results are discussed in terms of the task requirements of dissociation between head and trunk rotations focusing on the hypothesis of sufficiency and higher relevance of information contained in biological motion models applied to learning of complex motor skills

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An experiment was conducted to investigate the persistence of the effect of ""bandwidth knowledge of results (KR)"" manipulated during the learning phase of performing a manual force-control task. The experiment consisted of two phases, an acquisition phase with the goal of maintaining 60% maximum force in 30 trials, and a second phase with the objective of maintaining 40% of maximum force in 20 further trials. There were four bandwidths of KR: when performance error exceeded 5, 10, or 15% of the target, and a control group (0% bandwidth). Analysis showed that 5, 10, and 15% bandwidth led to better performance than 0% bandwidth KR at the beginning of the second phase and persisted during the extended trials.

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Active control solutions appear to be a feasible approach to cope with the steadily increasing requirements for noise reduction in the transportation industry. Active controllers tend to be designed with a target on the sound pressure level reduction. However, the perceived control efficiency for the occupants can be more accurately assessed if psychoacoustic metrics can be taken into account. Therefore, this paper aims to evaluate, numerically and experimentally, the effect of a feedback controller on the sound quality of a vehicle mockup excited with engine noise. The proposed simulation scheme is described and experimentally validated. The engine excitation is provided by a sound quality equivalent engine simulator, running on a real-time platform that delivers harmonic excitation in function of the driving condition. The controller performance is evaluated in terms of specific loudness and roughness. It is shown that the use of a quite simple control strategy, such as a velocity feedback, can result in satisfactory loudness reduction with slightly spread roughness, improving the overall perception of the engine sound. (C) 2008 Elsevier Ltd. All rights reserved.

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One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

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This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

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This paper reports the use of a non-destructive, continuous magnetic Barkhausen noise (CMBN) technique to investigate the size and thickness of volumetric defects, in a 1070 steel. The magnetic behavior of the used probe was analyzed by numerical simulation, using the finite element method (FEM). Results indicated that the presence of a ferrite coil core in the probe favors MBN emissions. The samples were scanned with different speeds and probe configurations to determine the effect of the flaw on the CMBN signal amplitude. A moving smooth window, based on a second-order statistical moment, was used for analyzing the time signal. The results show the technique`s good repeatability, and high capacity for detection of this type of defect. (C) 2009 Elsevier Ltd. All rights reserved.

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The magnetic Barkhausen energy in the rolling and transversal directions of AISI/SAE 1070 annealed surfaces is studied. The measurements were made in the samples under applied tension in the elastic-plastic region for different angular directions. The outcomes evidence that the magnetic anisotropy coefficient can be used to characterize the linear and nonlinear elastic limits of the material tinder tensile tresses. The results also show that the area of the curve corresponding to the angular dependence of the number of Barkhausen jumps with average energy presents a maximum value that corresponds to the elastic limit of the sample. (C) 2008 Elsevier Ltd. All rights reserved.

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The present work shows measurements of the Magnetic Barkhausen Noise (MBN) in commercial AISI/SAE 1045 and ASTM 36 steel deformed samples. The correlation between the MBN root mean square, Barkhausen signal profile and MBN power spectrum with the plastic deformation is established. The results show that the power spectral density of the Barkhausen signal is more effective as nondestructive evaluator than root mean square of Barkhausen signal. The Outcomes also suggest the presence of unbalanced tensions between the surface and the bulk of sample due to the presence of plastic deformation.

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The present work presents the measurements of the magnetic Barkhausen noise (MBN) in ASTM 36 steel samples around a pit under plastic deformation. The contour maps obtained from these Barkhausen noise measurements are compared with the finite element analysis of the ideal plastic deformation. Also, a parameter of the Barkhausen signal to detect the plastic deformation around the pit in ASTM 36 steel is obtained. Additionally to that, we propose another MBN parameter to estimate the pit width using the Barkhausen noise. (c) 2007 Elsevier Ltd. All rights reserved.

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The impact of the titanium nitride (TIN) gate electrode thickness has been investigated in n and p channel SOI multiple gate field effect transistors (MuGFETs) through low frequency noise charge pumping and static measurements as well as capacitance-voltage curves The results suggest that a thicker TIN metal gate electrode gives rise to a higher EOT a lower mobility and a higher interface trap density The devices have also been studied for different back gate biases where the GIFBE onset occurs at lower front-gate voltage for thinner TIN metal gate thickness and at higher V(GF) In addition it is demonstrated that post deposition nitridation of the MOCVD HfSiO gate dielectric exhibits an unexpected trend with TIN gate electrode thickness where a continuous variation of EOT and an increase on the degradation of the interface quality are observed (C) 2010 Elsevier Ltd All rights reserved

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We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

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In this work we explore the noise characteristics in lithographically-defined two terminal devices containing self-assembled InAs/InP quantum dots. The experimental ensemble of InAs dots show random telegraph noise (RTN) with tuneable relative amplitude-up to 150%-in well defined temperature and source-drain applied voltage ranges. Our numerical simulation indicates that the RTN signature correlates with a very low number of quantum dots acting as effective charge storage centres in the structure for a given applied voltage. The modulation in relative amplitude variation can thus be associated to the altered electrostatic potential profile around such centres and enhanced carrier scattering provided by a charged dot.