PATTERN RECOGNITION AND IMAGE ANALYSIS最新文献_第6页

I.G. Persiantsev’s Scientific School at the Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics: History of Development and Overview of Key Works 莫斯科国立罗蒙诺索夫大学斯科别尔琴核物理研究所 I.G. 佩尔相采夫科学院：发展历史和主要成果概述

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040132

S. A. Dolenko

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Earth Remote Sensing and Geographic Information Systems 地球遥感和地理信息系统

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040454

V. A. Soifer, V. V. Sergeev, V. N. Kopenkov, A. V. Chernov

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Optimization in Automation Systems for Design and Management: Scientific and Pedagogical School of Dmitry Ivanovich Batishchev 自动化系统的优化设计与管理》：德米特里-伊万诺维奇-巴蒂什切夫科学与师范学校

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040041

L. G. Afraimovich, P. D. Basalin, A. G. Korotchenko, M. Kh. Prilutskii, N. V. Starostin

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Ural School of Pattern Recognition: Majoritarian Approach to Ensemble Learning 乌拉尔模式识别学院：集合学习的多数派方法

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040314

Vl. D. Mazurov, M. I. Poberii, M. Yu. Khachai

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Systems for Recognition and Intelligent Analysis of Biomedical Images 生物医学图像识别和智能分析系统

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s105466182304020x

N. Yu. Ilyasova, N. S. Demin

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Scientific School “Models and Methods for Processing Video Information of Spatially Distributed Data, Pattern Recognition, Geoinformation Technologies” 科学院 "处理空间分布数据视频信息的模型和方法、模式识别、地理信息技术"

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s105466182304051x

D. Yu. Vasin

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Pattern Recognition and Concept Analysis 模式识别和概念分析

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040260

V. K. Leontiev

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Dynamics, Mechanics, Control, and Mathematical Modeling–Scientific and Pedagogical School of Yuri Isaakovich Neimark 动力学、力学、控制和数学建模--尤里-伊萨科维奇-奈马克科学与师范学院

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040399

V. P. Savelyev, D. Yu. Vasin

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Developing the Theory of Stochastic Canonic Expansions and Its Applications 发展随机卡农展开理论及其应用

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040429

I. N. Sinitsyn

{"title":"Developing the Theory of Stochastic Canonic Expansions and Its Applications","authors":"I. N. Sinitsyn","doi":"10.1134/s1054661823040429","DOIUrl":"https://doi.org/10.1134/s1054661823040429","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The creation of the theory of canonic expansions (CEs) is related with the names Loeve, Kolmogorov, Karhunen, and Pugachev and dates back to the 1940–1950s. The development of the theory of CEs and wavelet CEs is considered in application to the problems of the analysis, modeling, and synthesis of stochastic systems (SSs) and technologies. The direct and inverse Pugachev theorems about CEs are extended to the case of stochastic linear functionals within the framework of the correlational theory of stochastic functions (SFs). The CEs of linear and quasi-linear SFs are derived. Particular attention is paid to the problems of the equivalent regression linearization of strongly nonlinear transformations by CEs. The nonlinear regression algorithms on the basis of CEs are proposed. The theory of wavelet CEs within the specified domain of the change of the argument on the basis of Haar wavelets is developed. For stochastic elements (SEs), the direct and inverse Pugachev theorems are formulated and the correlational theory of joint CEs for two SEs is developed together with the theory of linear transformations. The solution of linear operator equations by the CEs of SEs in linear spaces with a basis is given. Special attention is focused on the CEs of SEs in Banach spaces with a basis. Some elements of the general theory of distributions for the CEs of SFs and SEs are developed. Particular attention is paid to the method based on CEs with independent components. Some new methods for the calculation of Radon–Nikodym derivatives are proposed. The considered applications of CEs and wavelet CEs to analysis, modeling, and synthesis problems are as follows: SSs and technologies, modeling, identification and recognition filtering, metrological and biometric technologies and systems, and synergic organizational technoeconomic systems (OTESs). The conclusion contains inferences and propositions for further studies. The list of references contains 43 items.</p>","PeriodicalId":35400,"journal":{"name":"PATTERN RECOGNITION AND IMAGE ANALYSIS","volume":"37 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140205398","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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Research Overview on Statistical Image Analysis Conducted at Ulyanovsk State Technical University 乌里扬诺夫斯克国立技术大学开展的图像统计分析研究概述

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PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI: 10.1134/s1054661823040508

K. K. Vasilyev, V. R. Krasheninnikov, A. G. Tashlinskii

引用次数: 0