Many types of automated visual surveillance systems have been presented in the recent literature. Most of the schemes require custom equipment, or involve significant complexity and storage needs. After studying the a...
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ISBN:
(纸本)9781479930807
Many types of automated visual surveillance systems have been presented in the recent literature. Most of the schemes require custom equipment, or involve significant complexity and storage needs. After studying the area in detail, this work presents four novel algorithms to perform automated, real-time intruder detection in surveillance networks. Built using machine learning techniques, the proposed algorithms are adaptive and portable, do not require any expensive or sophisticated component, are lightweight, and efficient with runtimes of the order of hundredths of a second. Two of the proposed algorithms have been developed by us. With application to two complementary data sets and quantitative performance comparisons with two representative existing schemes, we show that it is possible to easily obtain high detection accuracy with low false positives.
We study the multi-armed bandit (MAB) problem with composite and anonymous feedback. In this model, the reward of pulling an arm spreads over a period of time (we call this period as reward interval) and the player re...
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ISBN:
(纸本)9781577358664
We study the multi-armed bandit (MAB) problem with composite and anonymous feedback. In this model, the reward of pulling an arm spreads over a period of time (we call this period as reward interval) and the player receives partial rewards of the action, convoluted with rewards from pulling other arms, successively. Existing results on this model require prior knowledge about the reward interval size as an input to their algorithms. In this paper, we propose adaptive algorithms for both the stochastic and the adversarial cases, without requiring any prior information about the reward interval. For the stochastic case, we prove that our algorithm guarantees a regret that matches the lower bounds (in order). For the adversarial case, we propose the first algorithm to jointly handle non-oblivious adversary and unknown reward interval size. We also conduct simulations based on real-world dataset. The results show that our algorithms outperform existing benchmarks.
We study problems in computational geometry from the viewpoint of adaptive algorithms. adaptive algorithms have been extensively studied for the sorting problem, and in this paper we generalize the framework to geomet...
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ISBN:
(纸本)9783642145520
We study problems in computational geometry from the viewpoint of adaptive algorithms. adaptive algorithms have been extensively studied for the sorting problem, and in this paper we generalize the framework to geometric problems. To this end, we think of geometric problems as permutation (or rearrangement) problems of arrays, and define the "presortedness" as a distance from the input array to the desired output array. We call an algorithm adaptive if it runs faster when a given input array is closer to the desired output, and furthermore it does not make use of any information of the presortedness. As a case study, we look into the planar convex hull problem for which we discover two natural formulations as permutation problems. An interesting phenomenon that we prove is that for one formulation the problem can be solved adaptively, but for the other formulation no adaptive algorithm can be better than an optimal output-sensitive algorithm for the planar convex hull problem.
Modem communication systems are designed to be robust while maximizing achieved capacity. To achieve this goal many standards allow the use a variety of coding schemes, constellations, error coding capabilities and ot...
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ISBN:
(纸本)0780375033
Modem communication systems are designed to be robust while maximizing achieved capacity. To achieve this goal many standards allow the use a variety of coding schemes, constellations, error coding capabilities and other transmission parameters. The actual transmission parameters in use should be tailored to the actual channel conditions. Hence, there is a need for algorithms that analyze channel impairments using digital signal processing methods and determine the optimal transmission parameters accordingly. Furthermore, as channel conditions vary over time, these algorithms should be adaptive. The capabilities of the receiver in use should be taken into consideration as well. In this paper we present the benefits of developing such adaptive algorithms and demonstrate them in several contemporary standards. In the case of cable modem communication we present a solution that employs Digital Signal Processor (DSP) based Upstream Channel Analysis (DUCA) adaptive algorithms. Simulation results of such adaptive algorithms conclude this paper.
Unattended ground sensors (UGS) in long-term distributed sensing deployments benefit greatly from the incorporation of unmanned aerial systems (UAS). For instance, the mobility of data-ferrying UAS may be leveraged to...
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In this report, we present adaptive algorithms of the real-time correlative analysis with the use of a moving (after each readout) window with control of stationarity. The control means checking mean values and disper...
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ISBN:
(纸本)0819431834
In this report, we present adaptive algorithms of the real-time correlative analysis with the use of a moving (after each readout) window with control of stationarity. The control means checking mean values and dispersion in floating ranges of confidence. Results of computer simulation illustrate how the algorithm works. Errors made while using the algorithm of a moving window are analysed. A structure of a new algorithm was presented. Software, created based on the algorithm, was used for computer simulation.
In this paper we revisit the fixed-confidence identification of the Pareto optimal set in a multi-objective multi-armed bandit model. As the sample complexity to identify the exact Pareto set can be very large, a rela...
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In the field of wireless communications effective and authentic usage of spectrum will be an added advantage to achieve the desired capacity for a communication system. So minimizing the interference within the channe...
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This paper deals with active noise control (ANC) for impulsive noise sources. The most famous filtered-x least mean square (FxLMS) algorithm for ANC systems, is based on minimization of the variance of the error signa...
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ISBN:
(纸本)9781618392800
This paper deals with active noise control (ANC) for impulsive noise sources. The most famous filtered-x least mean square (FxLMS) algorithm for ANC systems, is based on minimization of the variance of the error signal. The impulsive noise can be modeled using non-Gaussian stable process for which second order moments do not exist. The FxLMS algorithm, therefore, becomes unstable for the impulsive noise. Among the existing adaptive algorithms for ANC of impulsive noise, one is based on the minimizing fractional lower order moment (p-power of error) that does exist for stable distributions, resulting in filtered-x least mean p-power (FxLMP) algorithm. Another solution is based on modifying;on the basis of statistical properties;the reference signal in the update equation of the FxLMS algorithm. In this paper, we discuss various variants of these two approaches. We see that using saturation nonlinearity in the reference and error signals of update equations of above-mentioned adaptive algorithms greatly improves the convergence performance. Yet as another solution, a modified normalized step-size may also be employed. Computer simulations demonstrate the effectiveness of the modified algorithms. We observe that the modified modifications greatly improve the robustness of existing adaptive algorithms for ANC of impulsive noise sources.
In this Ph. D. thesis we develop equilibrated? ux a posteriori error estimates for poro-mechanical and poro-plasticity problems. Based on these estimations we propose adaptive algorithms for the numerical solution of ...
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In this Ph. D. thesis we develop equilibrated? ux a posteriori error estimates for poro-mechanical and poro-plasticity problems. Based on these estimations we propose adaptive algorithms for the numerical solution of problems in soil mechanics. The? rst chapter deals with linear poro-elasticity problems. Using equilibrated Hpdivq-conforming? ux reconstructions of the Darcy velocity and the mechanical stress tensor, we obtain a guar- anteed upper bound on the error. We apply this estimate in an adaptive algorithm balancing the space and time discretisation error components in simulations in two space dimensions. The main contribution of this chapter is the symmetric reconstruction of the stress tensor. In the second chapter we propose another reconstruction technique for the stress tensor, while considering nonlinear elasticity problems. By imposing the symmetry of the tensor only weakly, we reduce computation time and simplify the implementation. We prove that the estimate obtained using this stress reconstuction is locally and globally e? cient for a wide range of hyperelasticity problems. We add a linearization error estimator, enabling us to introduce adaptive stopping criteria for the linearization solver. The third chapter adresses the industrial application of the obtained results. We apply an adaptive algorithm to three-dimensional poro-mechanical problems involving elasto-plastic me- chanical behavior laws.
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