Search Results - "Martins, Allan M"
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Complex Correntropy: Probabilistic Interpretation and Application to Complex-Valued Data
Published in IEEE signal processing letters (01-01-2017)“…Recent studies have demonstrated that correntropy is an efficient tool for analyzing higher order statistical moments in non-Gaussian noise environments…”
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Electroencephalography Signal Analysis for Human Activities Classification: A Solution Based on Machine Learning and Motor Imagery
Published in Sensors (Basel, Switzerland) (26-04-2023)“…Electroencephalography (EEG) is a fundamental tool for understanding the brain's electrical activity related to human motor activities. Brain-Computer…”
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An adaptive kernel width convex combination method for maximum correntropy criterion
Published in Journal of the Brazilian Computer Society (01-12-2021)“…Recently, the maximum correntropy criterion (MCC) has been successfully applied in numerous applications regarding nonGaussian data processing. MCC employs a…”
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Performance evaluation of the maximum complex correntropy criterion with adaptive kernel width update
Published in EURASIP journal on advances in signal processing (08-11-2019)“…The complex correntropy is a recently defined similarity measure that extends the advantages of conventional correntropy to complex-valued data. As in the…”
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Complex Correntropy Applied to a Compressive Sensing Problem in an Impulsive Noise Environment
Published in IEEE access (2019)“…Correntropy is a similarity function capable of extracting high-order statistical information from data. It has been used in different kinds of applications as…”
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Performance evaluation of the correntropy coefficient in automatic modulation classification
Published in Expert systems with applications (01-01-2015)“…•We propose the direct use of the correntropy for modulation format recognition.•We investigate the influence of kernel size on the performance of the…”
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Cyclostationary correntropy: Definition and applications
Published in Expert systems with applications (01-03-2017)“…•We propose a new mathematical tool for the higher-order cyclostationary analysis.•We define the Cyclic Correntropy Function (CCF) of random process.•We…”
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Automatic Modulation Classification Architectures Based on Cyclostationary Features in Impulsive Environments
Published in IEEE access (2019)“…Cyclostationary analysis has several applications in communications, e.g., spectral sensing, signal parameter estimation, and modulation classification. Most…”
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Circular Correntropy: Definition and Application in Impulsive Noise Environments
Published in IEEE access (2022)“…Circular statistics has been applied to several areas of knowledge in which the input data is circular or directional. Noisy measurements are still a problem…”
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NARX Model Identification Using Correntropy Criterion in the Presence of Non-Gaussian Noise
Published in Journal of control, automation & electrical systems (15-08-2019)“…In past years, the system identification area has emphasized the identification of nonlinear dynamic systems. In this field, polynomial nonlinear…”
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Complex correntropy function: Properties, and application to a channel equalization problem
Published in Expert systems with applications (01-10-2018)“…•We define a new generalized similarity measure between complex random variables.•A complete deduction is presented and important properties are…”
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Complex Correntropy Induced Metric Applied to Compressive Sensing with Complex-Valued Data
Published in 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) (01-04-2018)“…The correntropy induced metric (CIM) is a well- defined metric induced by the correntropy function and has been applied to different problems in signal…”
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Conference Proceeding -
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Corrigendum to “Cyclostationary Correntropy: Definition and applications” [Expert Systems with Applications 69 (2017) 110–117]
Published in Expert systems with applications (15-09-2017)Get full text
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Variance fluctuations in nonstationary time series: a comparative study of music genres
Published in Physica A (15-05-2004)“…An important problem in physics concerns the analysis of audio time series generated by transduced acoustic phenomena. Here, we develop a new method to…”
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Retail sales forecasting for a Brazilian supermarket chain: an empirical assessment
Published in 2022 IEEE 24th Conference on Business Informatics (CBI) (01-06-2022)“…Time series forecasting is a consolidated, broadly used approach in several fields, such as finance and industry. Retail can also benefit from forecasting in…”
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Conference Proceeding -
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Controlling epidemic diseases based only on social distancing level
Published 16-05-2020“…The World Health Organization (WHO) made the assessment that COVID-19 can be characterized as a pandemic on March 11, 2020. To the COVID-19 outbreak, there is…”
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Performance evaluation of the maximum correntropy criterion in identification systems
Published in 2016 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) (01-05-2016)“…The System identification explores ways to obtain mathematical models of an unknown system. However, as a result from the intrinsic random nature of system or…”
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Conference Proceeding -
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Planar target following control scheme based on path generation for nonholonomic terrestrial robots
Published in 2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) (01-11-2017)“…This paper addresses the problem of controlling the posture of a dual wheeled mobile terrestrial robot, with movement constraints with the objective of detect…”
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Data driven monitoring and 3D visualization for hydro refining industrial processes
Published in 2016 IEEE 25th International Symposium on Industrial Electronics (ISIE) (01-06-2016)“…This paper addresses the issue of monitoring and diagnosis on hydro refining industrial processes. The main contribution in this work is the use of a 3D model…”
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Conference Proceeding -
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Clustering using neural networks and Kullback-Leibler divergency
Published in 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541) (2004)“…In this work we develop a clustering algorithm based on Kullback-Leibler divergence as the dissimilarity measurement. That measure is used with an algorithm…”
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Conference Proceeding