Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-285-292
D. Murashov, Y. Obukhov, I. Kershner, M. Sinkin
In this paper, a technique for automated detecting diagnostic events in the video channel of video and electroencephalographic monitoring data is presented. The technique is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed at detecting a group of frames characterized by high activity of frame regions. For detecting the frames, a criterion computed from the optical flow is proposed. The preliminary results of the analysis of real clinical data are presented. The intervals of synchronous muscle and brain activity, which may correspond to an epileptic seizure, are detected. These intervals can be used for diagnosing epileptic seizures and distinguishing them from non-epileptic events. Requirements for video shooting conditions are formulated.
{"title":"A technique for detecting diagnostic events in video channel of synchronous video and electroencephalographic monitoring data","authors":"D. Murashov, Y. Obukhov, I. Kershner, M. Sinkin","doi":"10.18287/1613-0073-2019-2391-285-292","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-285-292","url":null,"abstract":"In this paper, a technique for automated detecting diagnostic events in the video channel of video and electroencephalographic monitoring data is presented. The technique is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed at detecting a group of frames characterized by high activity of frame regions. For detecting the frames, a criterion computed from the optical flow is proposed. The preliminary results of the analysis of real clinical data are presented. The intervals of synchronous muscle and brain activity, which may correspond to an epileptic seizure, are detected. These intervals can be used for diagnosing epileptic seizures and distinguishing them from non-epileptic events. Requirements for video shooting conditions are formulated.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85111188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-97-102
N. Glumov, M. Gashnikov
We consider the compression of multidimensional signals on the aircraft board. We describe the data of such signals as a hypercube, which is "rotated" in a special way. To compress this hypercube, we use a hierarchical compression method. As one of the stages of this method, we use an adaptive interpolation algorithm. The adaptive algorithm automatically switches between different interpolating functions at each signal point. We perform computational experiments in real-world multidimensional signals. Computational experiments confirm that the use of proposed adaptive interpolator allows increasing (up to 31%) the compression ratio of the “rotated” hypercube corresponding to multidimensional hyperspectral signals.
{"title":"Adaptive interpolation of multidimensional signals for compression on board an aircraft","authors":"N. Glumov, M. Gashnikov","doi":"10.18287/1613-0073-2019-2391-97-102","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-97-102","url":null,"abstract":"We consider the compression of multidimensional signals on the aircraft board. We describe the data of such signals as a hypercube, which is \"rotated\" in a special way. To compress this hypercube, we use a hierarchical compression method. As one of the stages of this method, we use an adaptive interpolation algorithm. The adaptive algorithm automatically switches between different interpolating functions at each signal point. We perform computational experiments in real-world multidimensional signals. Computational experiments confirm that the use of proposed adaptive interpolator allows increasing (up to 31%) the compression ratio of the “rotated” hypercube corresponding to multidimensional hyperspectral signals.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87969173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-209-218
O. Pavlov
The article explores the incentive problem of executors of the new products development project at the industrial enterprise in continuous time. In the process of developing new products, the learning curve effect manifests itself, which leads to a reduction in labor intensity, depending on the cumulative volume of production. The project for the new products development is considered as a managed hierarchical dynamic system, consisting of a project management board (principal) and executors (agents). The interaction of project participants is formalized as a hierarchical differential game. To solve the formulated dynamic problem of material incentives, the well-known principle of cost compensation was applied. The original problem is divided into the task of coordinated incentives and the task of coordinated planning. The study showed that the task of coordinated dynamic planning is for the principal to determine the optimal planned production volumes in order to minimize the labor cost of agents. The initial dynamic problem of material incentives was reduced to the optimal control problem. The problem of optimal control with continuous time was solved analytically using the Pontryagin maximum principle. The study identifies a condition to determine the optimal production volumes for coordination of the interests of the principal and agents.
{"title":"Dynamic game task of executors incentives in projects for the development of new production in continuous time","authors":"O. Pavlov","doi":"10.18287/1613-0073-2019-2416-209-218","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-209-218","url":null,"abstract":"The article explores the incentive problem of executors of the new products development project at the industrial enterprise in continuous time. In the process of developing new products, the learning curve effect manifests itself, which leads to a reduction in labor intensity, depending on the cumulative volume of production. The project for the new products development is considered as a managed hierarchical dynamic system, consisting of a project management board (principal) and executors (agents). The interaction of project participants is formalized as a hierarchical differential game. To solve the formulated dynamic problem of material incentives, the well-known principle of cost compensation was applied. The original problem is divided into the task of coordinated incentives and the task of coordinated planning. The study showed that the task of coordinated dynamic planning is for the principal to determine the optimal planned production volumes in order to minimize the labor cost of agents. The initial dynamic problem of material incentives was reduced to the optimal control problem. The problem of optimal control with continuous time was solved analytically using the Pontryagin maximum principle. The study identifies a condition to determine the optimal production volumes for coordination of the interests of the principal and agents.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91534378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-180-186
N. Abramov, А. А. Talalayev, V. Fralenko, O. Shishkin, V. Khachumov
The paper introduces how multi-class and single-class problems of searching and classifying target objects in remote sensing images of the Earth are solved. To improve the recognition efficiency, the preparation tools for training samples, optimal configuration and use of deep learning neural networks using high-performance computing technologies have been developed. Two types of CNN were used to process ERS images: a convolutional neural network from the nnForge library and a network of the Darknet type. A comparative analysis of the results is obtained. The research showed that the capabilities of convolutional neural networks allow solving simultaneously the problems of searching (localizing) and recognizing objects in ERS images with high accuracy and completeness.
{"title":"Neural network technology to search for targets in remote sensing images of the Earth","authors":"N. Abramov, А. А. Talalayev, V. Fralenko, O. Shishkin, V. Khachumov","doi":"10.18287/1613-0073-2019-2391-180-186","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-180-186","url":null,"abstract":"The paper introduces how multi-class and single-class problems of searching and classifying target objects in remote sensing images of the Earth are solved. To improve the recognition efficiency, the preparation tools for training samples, optimal configuration and use of deep learning neural networks using high-performance computing technologies have been developed. Two types of CNN were used to process ERS images: a convolutional neural network from the nnForge library and a network of the Darknet type. A comparative analysis of the results is obtained. The research showed that the capabilities of convolutional neural networks allow solving simultaneously the problems of searching (localizing) and recognizing objects in ERS images with high accuracy and completeness.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74702346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-57-62
A. Agafonov, A. Yumaganov
The problem of predicting the movement of public transport is one of the most popular problems in the field of transport planning due to its practical significance. Various parametric and non-parametric models are used to solve this problem. In this paper, heterogeneous information affecting the prediction value is used to predict the arrival time of public transport, and a comparison of the main machine learning algorithms for the public transport arrival time forecasting is given: neural networks, support vector regression. An experimental analysis of the algorithms was carried out on real traffic information about bus routes in Samara, Russia.
{"title":"Performance comparison of machine learning methods in the bus arrival time prediction problem","authors":"A. Agafonov, A. Yumaganov","doi":"10.18287/1613-0073-2019-2416-57-62","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-57-62","url":null,"abstract":"The problem of predicting the movement of public transport is one of the most popular problems in the field of transport planning due to its practical significance. Various parametric and non-parametric models are used to solve this problem. In this paper, heterogeneous information affecting the prediction value is used to predict the arrival time of public transport, and a comparison of the main machine learning algorithms for the public transport arrival time forecasting is given: neural networks, support vector regression. An experimental analysis of the algorithms was carried out on real traffic information about bus routes in Samara, Russia.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"100 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75171574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-271-276
Y. Kropotov, A. Belov, A Y Prockuryakov
The paper deals with the issues of increasing signal/noise ratio in telecommunication audio exchange systems. The study of characteristics of speech signals and acoustic noises, such as mathematical expectation, dispersion, relative intensity of acoustic speech signals and various types of acoustic noises and interference is carried out. It is shown that in the design of telecommunications systems, in particular loudspeaker systems operating under the influence of external acoustic noise of high intensity, it is necessary to solve the problem of developing algorithms to effectively suppress the above mentioned interference to ensure the necessary signal/noise ratio in communication systems. A mathematical model of the autocorrelation function of the speech signal by using the Lagrange interpolation polynomial of order 10, considered the creation of adaptive algorithms to suppress acoustic noise by linear filtering methods. Thus suppression of acoustic noises and hindrances is possible at the expense of operated change of area of a cutting in the interval from 0 Hz to 300-1000 Hz, depending on a hindrance conditions.
{"title":"Increasing signal/acoustic interference ratio in telecommunications audio exchange by adaptive filtering methods","authors":"Y. Kropotov, A. Belov, A Y Prockuryakov","doi":"10.18287/1613-0073-2019-2416-271-276","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-271-276","url":null,"abstract":"The paper deals with the issues of increasing signal/noise ratio in telecommunication audio exchange systems. The study of characteristics of speech signals and acoustic noises, such as mathematical expectation, dispersion, relative intensity of acoustic speech signals and various types of acoustic noises and interference is carried out. It is shown that in the design of telecommunications systems, in particular loudspeaker systems operating under the influence of external acoustic noise of high intensity, it is necessary to solve the problem of developing algorithms to effectively suppress the above mentioned interference to ensure the necessary signal/noise ratio in communication systems. A mathematical model of the autocorrelation function of the speech signal by using the Lagrange interpolation polynomial of order 10, considered the creation of adaptive algorithms to suppress acoustic noise by linear filtering methods. Thus suppression of acoustic noises and hindrances is possible at the expense of operated change of area of a cutting in the interval from 0 Hz to 300-1000 Hz, depending on a hindrance conditions.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"171 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75097861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-233-242
A Y Denisova, L. M. Kavelenova, E. Korchikov, A. Pomogaybin, N. Prokhorova, D. A. Terentyeva, V. Fedoseev, N. Yankov
The forest and shrub communities are important components of the environment and provide a wide spectrum of ecological services. In the Samara region the forest and shrub cover is dispersed on the territory what makes its monitoring difficult. The forest areas are limited by natural and anthropogenic reasons since Samara region is a forest-steppe territory with a high level of human activity. The shrub communities are mostly the secondary ecosystems incorporated in natural grassy communities, agricultural fields or enclosing to forests. These specific ecosystems can be recognized on remote sensing data including satellite images supported by preliminary ground surveys. In this article, we present the study of the forest and shrub communities recognition using remote sensing images and ground surveys in the Samara region. We describe a process of the test site selection for remote sensing data verification and discuss the results of applying the author’s classification technology for multispectral remote sensing composites to classify forest communities in the Samara region
{"title":"Recognition of forest and shrub communities on the base of remotely sensed data supported by ground studies","authors":"A Y Denisova, L. M. Kavelenova, E. Korchikov, A. Pomogaybin, N. Prokhorova, D. A. Terentyeva, V. Fedoseev, N. Yankov","doi":"10.18287/1613-0073-2019-2391-233-242","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-233-242","url":null,"abstract":"The forest and shrub communities are important components of the environment and provide a wide spectrum of ecological services. In the Samara region the forest and shrub cover is dispersed on the territory what makes its monitoring difficult. The forest areas are limited by natural and anthropogenic reasons since Samara region is a forest-steppe territory with a high level of human activity. The shrub communities are mostly the secondary ecosystems incorporated in natural grassy communities, agricultural fields or enclosing to forests. These specific ecosystems can be recognized on remote sensing data including satellite images supported by preliminary ground surveys. In this article, we present the study of the forest and shrub communities recognition using remote sensing images and ground surveys in the Samara region. We describe a process of the test site selection for remote sensing data verification and discuss the results of applying the author’s classification technology for multispectral remote sensing composites to classify forest communities in the Samara region","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72679621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-103-108
G. Safina, A. Tashlinskii, M. Tsaryov
The paper is devoted to the analysis of the possibilities of using Markov chains for analyzing the accuracy of stochastic gradient relay estimation of image geometric deformations. One of the ways to reduce computational costs is to discretize the domain of studied parameters. This approach allows to choose the dimension of transition probabilities matrix a priori. However, such a matrix has a rather complicated structure. It does not significantly reduce the number of computations. A modification of the transition probabilities matrix is proposed, it’s dimension does not depend on the dimension of estimated parameters vector. In this case, the obtained relations determine a recurrent algorithm for calculating the matrix at the estimation iterations. For the one-step transitions matrix, the calculated expressions for the probabilities of image deformation parameters estimates drift are given.
{"title":"Adaptation of the mathematical apparatus of the Markov chain theory for the probabilistic analysis of recurrent estimation of image inter-frame geometric deformations","authors":"G. Safina, A. Tashlinskii, M. Tsaryov","doi":"10.18287/1613-0073-2019-2391-103-108","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-103-108","url":null,"abstract":"The paper is devoted to the analysis of the possibilities of using Markov chains for analyzing the accuracy of stochastic gradient relay estimation of image geometric deformations. One of the ways to reduce computational costs is to discretize the domain of studied parameters. This approach allows to choose the dimension of transition probabilities matrix a priori. However, such a matrix has a rather complicated structure. It does not significantly reduce the number of computations. A modification of the transition probabilities matrix is proposed, it’s dimension does not depend on the dimension of estimated parameters vector. In this case, the obtained relations determine a recurrent algorithm for calculating the matrix at the estimation iterations. For the one-step transitions matrix, the calculated expressions for the probabilities of image deformation parameters estimates drift are given.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75500190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-160-168
A. Kornilov, I. Safonov, A. V. Goncharova, I. Yakimchuk
We present an algorithm for processing of X-ray microtomographic (micro-CT) images that allows automatic selection of a sub-volume having the best visual quality for further mathematical simulation, for example, flow simulation. Frequently, an investigated sample occupies only a part of a volumetric image or the sample can be into a holder; a part of the image can be cropped. For each 2D slice across the Z-axis of an image, the proposed method locates a region corresponding to the sample. We explored applications of several existing blind quality measures for an estimation of the visual quality of a micro-CT image slice. Some of these metrics can be applied to ranking the image regions according to their quality. Our method searches for a cubic area located inside regions belonging to the sample and providing the maximal sum of the quality measures of slices crossing the cube across the Z-axis. The proposed technique was tested on synthetic and real micro-CT images of rocks.
{"title":"Selection in a 3D microtomographic image the region with the highest quality","authors":"A. Kornilov, I. Safonov, A. V. Goncharova, I. Yakimchuk","doi":"10.18287/1613-0073-2019-2391-160-168","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-160-168","url":null,"abstract":"We present an algorithm for processing of X-ray microtomographic (micro-CT) images that allows automatic selection of a sub-volume having the best visual quality for further mathematical simulation, for example, flow simulation. Frequently, an investigated sample occupies only a part of a volumetric image or the sample can be into a holder; a part of the image can be cropped. For each 2D slice across the Z-axis of an image, the proposed method locates a region corresponding to the sample. We explored applications of several existing blind quality measures for an estimation of the visual quality of a micro-CT image slice. Some of these metrics can be applied to ranking the image regions according to their quality. Our method searches for a cubic area located inside regions belonging to the sample and providing the maximal sum of the quality measures of slices crossing the cube across the Z-axis. The proposed technique was tested on synthetic and real micro-CT images of rocks.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75849683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-31-40
M. Gashnikov
In this paper, we consider the interpolation of multidimensional signals problem. We develop adaptive interpolators that select the most appropriate interpolating function at each signal point. Parameterized decision rule selects the interpolating function based on local features at each signal point. We optimize the adaptive interpolator in the parameter space of this decision rule. For solving this optimization problem, we reduce the dimension of the parametric space of the decision rule. Dimension reduction is based on the parameterization of the ratio between local differences at each signal point. Then we optimize the adaptive interpolator in parametric space of reduced dimension. Computational experiments to investigate the effectiveness of an adaptive interpolator are conducted using real-world multidimensional signals. The proposed adaptive interpolator used as a part of the hierarchical compression method showed a gain of up to 51% in the size of the archive file compared to the smoothing interpolator.
{"title":"Interpolation of multidimensional signals using the reduction of the dimension of parametric spaces of decision rules","authors":"M. Gashnikov","doi":"10.18287/1613-0073-2019-2391-31-40","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-31-40","url":null,"abstract":"In this paper, we consider the interpolation of multidimensional signals problem. We develop adaptive interpolators that select the most appropriate interpolating function at each signal point. Parameterized decision rule selects the interpolating function based on local features at each signal point. We optimize the adaptive interpolator in the parameter space of this decision rule. For solving this optimization problem, we reduce the dimension of the parametric space of the decision rule. Dimension reduction is based on the parameterization of the ratio between local differences at each signal point. Then we optimize the adaptive interpolator in parametric space of reduced dimension. Computational experiments to investigate the effectiveness of an adaptive interpolator are conducted using real-world multidimensional signals. The proposed adaptive interpolator used as a part of the hierarchical compression method showed a gain of up to 51% in the size of the archive file compared to the smoothing interpolator.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83588188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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