Power factor correction converters are used in many applications as AC-DC power supplies aiming at maintaining a near unity power factor. Systems of this type are known to exhibit nonlinear phenomena such as sub-harmo...
Power factor correction converters are used in many applications as AC-DC power supplies aiming at maintaining a near unity power factor. Systems of this type are known to exhibit nonlinear phenomena such as sub-harmonic oscillations and chaotic regimes that cannot be described by traditional averaged models. In this paper, we derive a time varying discretetime map modeling the behavior of a power factor correction AC-DC boost converter. This map is derived in closed-form and is able to faithfully reproduce the system behavior under realistic conditions. In the chaotic regime the map exhibits a sequence of bifurcation similar to a bandcount doubling cascade on the low frequency. However, the observed scenario appears in some sense incomplete, with some gaps in the bifurcation diagram, whose appearance to our knowledge has never been reported before. We show that these gaps are caused by high frequency oscillations.
Starting from the user’s requirements previously defined, a new soft robotics approach was chosen and developed in order to overcome the criticalities arisen in the analysis of the state of the art. One of the key po...
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In this chapter we wrap up our literature investigation, pointing out the key focuses and requirements to be considered. We will go through our evaluations upon actuators, sensors, control systems and we will present ...
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The chapter presents the design of the device actuators and sensors in terms of concept developing, dimensioning, testing and prototyping. Inspired by soft robotics concept, the design of actuators is based on the cha...
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Effective spectrum sensing strategies enable cognitive radios to enhance the spectrum efficiency. In this paper, modeling, performance analysis, and optimization of spectrum handoff in a centralized cognitive radio ne...
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Hysteretic noisy chaotic neural network (HNCNN) has been proven to be a powerful tool in solving combinatorial optimization problems, which can increase the effective convergence toward optimal or near-optimal solutio...
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In this paper, we consider input-affine invertible MIMO nonlinear systems which can be transformed into a special normal form by means of the structure algorithm. The normal form highlights a partial state, a subset o...
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A fast sphere extraction method is proposed in this paper. The proposed method utilizes the one-dimensional histogram as search space. The polytope method, which is one of the minimization algorithms, is employed for ...
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A fast sphere extraction method is proposed in this paper. The proposed method utilizes the one-dimensional histogram as search space. The polytope method, which is one of the minimization algorithms, is employed for search parameters. The histogram has two characteristics. (a) The distribution of the histogram changes if the parameters of representing the sphere change. (b) The value of highest frequency of histogram becomes maximum if the best parameters are obtained. By employing the polytope method, the best parameters of sphere can be obtained when we get the highest frequency of histogram. The proposed method can extract the sphere from 3D vertex data without large memory space or long processing time.
Generalized Eigenvalues Classifiers (GEC), which originated from the GEPSVM algorithm by Mangasarian, proved to be an efficient alternative to the Support Vector Machines (SVMs) in the solution of supervised classific...
Generalized Eigenvalues Classifiers (GEC), which originated from the GEPSVM algorithm by Mangasarian, proved to be an efficient alternative to the Support Vector Machines (SVMs) in the solution of supervised classification tasks. However real-life datasets are often characterized by a large number of redundant features and by a great number of points whose labels are difficult (or too expensive) to assign. In this work we start from the Regularized Generalized Eigenvalue Classifier (ReGEC) and show how regularization terms can be used to enable the classifier to solve two different problems, strictly connected to that of supervised classification: feature selection and semi-supervised classification. Numerical results, obtained on some standard benchmark data sets, show the efficiency of the proposed solutions.
Hourly PM2.5 concentrations were observed simultaneously at a cities-cluster comprising 10 cities/towns in Hebei province in China from July 1 to 31, 2008. Among the 10 cities/towns, Baoding showed the high- est avera...
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Hourly PM2.5 concentrations were observed simultaneously at a cities-cluster comprising 10 cities/towns in Hebei province in China from July 1 to 31, 2008. Among the 10 cities/towns, Baoding showed the high- est average concentration level (161.57μg/m3) and Yanjiao exhibited the lowest (99.35 μg/m3 ). These observed data were also studied using the joint potential source contribution function with 24-h and 72-h backward trajectories, to identify more clearly the local and countrywide-scale long-range transport sources. For the local sources, three important influential areas were found, whereas five important influential areas were defined for long-range transport sources. Spatial characteristics of PM2.5 were determined by multivariate statistical analyses. Soil dust, coal combustion, and vehicle emissions might be the potential contributors in these areas. The results of a hierarchical cluster analysis for back trajectory endpoints and PM2.s concentrations datasets show that the spatial characteristics of PM2.5 in the cities-cluster were influenced not only by local sources, but also by long-range transport sources. Different cities in the cities-cluster obtained different weighted contributions from local or long-range transport sources. Cangzhou, Shijiazhuang, and Baoding are near the source areas in the south of Hebei province, whereas Zhuozhou, Yangfang, Yanjiao, Xianghe, and Langfang are close to the sources areas near Beijing and Tianjin.
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