Identification information sensors of robot systems

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dc.contributor.authorParkhomey, Igor
dc.contributor.authorBoiko, Juliy
dc.contributor.authorEromenko, Oleksander
dc.date.accessioned2019-05-18T06:05:15Z
dc.date.available2019-05-18T06:05:15Z
dc.date.issued2019-06
dc.descriptionIn this paper, the process of identification is considered in the case of incomplete input information. The complexity of this process is to find such a description in which the image (information) of each class would have defined similar properties. The problem of finding the optimal decisive rule arises, which in some cases can be constructed on the basis of a method based on the definition of the maximum incomplete coefficient of similarity. To eliminate the influence of interference on the recognition process, special decision rules are introduced. One of them is based on the fact that the decision on the belonging of the image to the image is made on the basis of the analysis of the images that fall into a certain close space, is classified. In this case, the decision takes into account the majority, which agrees well with the results obtained by calculating the similarity coefficient. This allows you to find solutions that are almost not sensitive to errors that occur due to interference.uk_UA
dc.description.abstractAt the present time, the complexity of identification is to find such a description, in which the image (information) of each class would have identified similar properties. The task is to make the transformed description includes the whole set of input images, united by the similarity class by the given ratio. Using the ordinates of an autocorrelation function is an inseparable shift in the center of gravity of an image, which leads to a change of such description. Nicest, the concept of an invariant description of information arises, this is an autocorrelation function, which is invariant to the description of any displacements of the image in the vertical and horizontal directions. The problem of finding an optimal decision rule arises, which, in a number of cases, can be constructed on the basis of a method, based on the definition of the maximum incomplete coefficient of similarity. Using this method, the solutions, that are almost unintelligible to the errors that arise due to the effects of interference, are found. Therefore, in increments k, this rule passes into the Bayes’ rule.uk_UA
dc.identifier.citationParkhomey I. Identification information sensors of robot systems / I. Parkhomey, J. Boiko, O. Eromenko // Indonesian Journal of Electrical Engineering and Computer Science. - 2019. - Vol.14, nr. 3. - P. 1235-1243.uk_UA
dc.identifier.issn2502-4752
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/7587
dc.language.isoenuk_UA
dc.publisherInstitute of Advanced Engineering and Scienceuk_UA
dc.subjectautocorrelation functionuk_UA
dc.subjectcoefficient of similarityuk_UA
dc.subjectdescription of imagesuk_UA
dc.subjectimage borderuk_UA
dc.subjectinvarianceuk_UA
dc.titleIdentification information sensors of robot systemsuk_UA
dc.typeСтаттяuk_UA
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Кафедра телекомунікацій, медійних та інтелектуальних технологій