In this paper, the robust finite-horizon filtering problem is investigated for a class of uncertain nonlinear discrete time-varying stochastic systems with multiple missing measurements and error variance constraints....
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ISBN:
(纸本)9781424451951
In this paper, the robust finite-horizon filtering problem is investigated for a class of uncertain nonlinear discrete time-varying stochastic systems with multiple missing measurements and error variance constraints. The stochastic nonlinearities are described by statistical means which can cover several classes of well-studied nonlinearities. The measurement missing phenomenon is also considered. Sufficient conditions are derived for a finite-horizon filter to satisfy the estimation error variance constraints. These conditions are expressed in terms of the feasibility of a series of recursive linear matrix inequalities (RLMIs). An illustrative simulation example is given to show the the effectiveness of the proposed algorithm.
Scheduling has a lot of applications in single machine operations. We can refer to its usage in computer and internet services. Many web requests may be replied to only through one path or router. One of the issues ra...
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ISBN:
(纸本)9781902316697
Scheduling has a lot of applications in single machine operations. We can refer to its usage in computer and internet services. Many web requests may be replied to only through one path or router. One of the issues raised, is to minimize the mean and variance of operations on jobs. In this paper, AL-Turki method is investigated for small jobs up to at most 10 static and dynamic jobs. First, different jobs with exponential distribution are produced and then all possible forms are investigated and the amount of the least function (the combination of mean & variance) is calculated for each one and finally the best response is chosen and compared with the previous method. The simulation results show that when the combined function is closer to the mean, it reaches the best response and the more the combined function is close to variance, it will have more distance from the optimal response. Moreover, we have extended the previous method and added a buffer between various stages of the jobs. The results show that adding buffer in the first stages helps us to get better response in most states of combined function. In this paper, two other important issues are taken into consideration. In the first state, according to the fact that in most timing matters, certain period of time is needed in each stage for decision making, we have added certain time units for decision making, and its effect has been investigated as well. Analysis of results indicate that increasing the decision making time would always cause the error between the amount of combined function and the optimum function to increase. In the second state, the Breakdown effect of the machine(breakdown time and breakdown duration) has been investigated. The analysis of simulation results show that these two parameters cause a deviation from the optimal results.
Most experimental realizations of quantum key distribution are based on the Bennett-Brassard 1984 (the so-called BB84) protocol. In a typical optical implementation of this scheme, the sender uses an active source to ...
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Most experimental realizations of quantum key distribution are based on the Bennett-Brassard 1984 (the so-called BB84) protocol. In a typical optical implementation of this scheme, the sender uses an active source to produce the required BB84 signal states. While active state preparation of BB84 signals is a simple and elegant solution in principle, in practice passive state preparation might be desirable in some scenarios, for instance, in those experimental setups operating at high transmission rates. Passive schemes might also be more robust against side-channel attacks than active sources. Typical passive devices involve parametric down-conversion. In this paper, we show that both coherent light and practical single-photon sources are also suitable for passive generation of BB84 signal states. Our method does not require any externally driven element, but only linear optical components and photodetectors. In the case of coherent light, the resulting key rate is similar to the one delivered by an active source. When the sender uses practical single-photon sources, however, the distance covered by a passive transmitter might be longer than that of an active configuration.
The social network analysis (SNA) is an approach that can be applied as a complement to other analysis (such as statistical) in order to obtain other valuable information. The social network analysis has been used in ...
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The social network analysis (SNA) is an approach that can be applied as a complement to other analysis (such as statistical) in order to obtain other valuable information. The social network analysis has been used in several initiatives showing that it is an approach that can contribute in building the semantic web. Within the project Technologies Applied to Electronics Teaching (TAEE) there are biannual conferences (it has been organized since 1996) and have accumulated a significant amount of data resulting from the conferences held. All of this information constitutes a data source that should be exploited and that can provide meaningful information. In this document we describe, how to social network analysis has been used on data sources generated by user communities, in order to obtain some semantic artifacts, like ontologies. Also describes how to was applied the social network analysis and its metrics on the information generated in the TAEE congresses to answer a set of questions (What are the relationships and the level of cohesion of the different organizations (at the level of Spain and across continents) involved in TAEE? How have evolutioned the thematics covered in the conference?, What are the new ontological additions in technology over the years?, and How have evolutioned the thematics in the research and studies related to teaching electronics?) formulated by the organizers of the congresses and that through other approaches would have been a large task and complicated. The answers to the questions can provide us important information about the behavior and characteristics of the elements present in TAEE conferences, furthermore being an element for making decisions on future initiatives with the same style of TAEE.
Cantilever vibration modes beyond the first harmonic of the standard flexural vibration mode were intensely explored in atomic force microscopy (AFM) during the past years. One example for this development is the usag...
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Extended models of the W-PESQ method are presented which are capable of assessing the subjective quality of noisy speech signals sampled at 48 kHz. Two methods are proposed: a version backward compatible with the W-PE...
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Extended models of the W-PESQ method are presented which are capable of assessing the subjective quality of noisy speech signals sampled at 48 kHz. Two methods are proposed: a version backward compatible with the W-PESQ standard, called EW-PESQ(E), and another, called EW-PESQ(R), in which the original psychoacoustic models are entirely replaced with alternative formulations available in the literature. Performance figures of both the EW-PESQ(E) and the EW-PESQ(R) in predicting the subjective quality of extrawide-band speech (sampled at 48 kHz) corrupted with broad-band and environmental noise are reported. In both cases the results obtained reveal a strong correlation (approximately 97%) with mean opinion scores.
This paper presents the solution of the global robust output regulation problem for a class of nonlinear systems with relative degree one without knowing the control direction. The result is also applied to an asympto...
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The experiments aimed to compare data driven models for the valuation of residential premises were conducted using KEEL (Knowledge Extraction based on Evolutionary Learning) system. Twelve different regression algorit...
The experiments aimed to compare data driven models for the valuation of residential premises were conducted using KEEL (Knowledge Extraction based on Evolutionary Learning) system. Twelve different regression algorithms were applied to an actual data set derived from the cadastral system and the registry of real estate transactions. The 10-fold cross validation and statistical tests were applied. The lowest values of MSE provided models constructed and optimized by means of support vector machine, artificial neural network, decision trees for regression and quadratic regression, however differences between them were not statistically significant. Worse performance revealed algorithms employing evolutionary fuzzy rule learning. The experiments confirmed the usefulness of KEEL as a powerful tool with its numerous evolutionary algorithms together with classical learning approaches to carry out laborious investigation on a practical problem in a relatively short time.
In order to provide the fastest search for optimal solution, both the structure and the parameters of genetic algorithms (GA) should be optimized. The advantage of recently introduced micro-genetic algorithms (μGA) i...
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The market economic system is a large complex system. In this paper, we define Four-Element Connection Numbers control which combines Set Pair Analysis, Extension Methods, etc, applies to economic control, which is ef...
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