使用广义光谱分析方法对生物医学和生物信息系统进行分析和分类

IF 0.7 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-03-20 DOI:10.1134/s1054661823040259

L. I. Kulikova, S. A. Makhortykh

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引用次数: 0

摘要

摘要概述了一种通用光谱分析方法--一种处理信息阵列的新方法。介绍了该方法的理论基础及其在各种实验数据处理问题以及生物医学和生物信息系统的分析、识别和诊断问题中的应用。举例说明了该方法在研究生物磁数据和生物大分子结构方面的应用。还提出了该方法在图像分析和识别中的应用问题。该方法的基础是在经典多项式和函数代数系统（Jacobi、Chebyshev、Lagrange、Laguerre 和 Gegenbauer 多项式等，具有一个和两个变量）以及球形函数的函数基础上对原始阵列进行自适应分解。这种方法结合了分析和数字数据处理程序，实际上是一种处理信息阵列的通用组合技术。

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Analysis and Classification of Biomedical and Bioinformation Systems Using a Generalized Spectral Analytical Approach

Abstract

A generalized spectral analytical method is outlined—a new approach to processing information arrays. The theoretical foundations of the method are presented, as well as its applications to various problems of processing of experimental data and problems of analysis, recognition, and diagnostics of biomedical and bioinformation systems. Examples of its use for studying biomagnetic data and structures of biomacromolecules are given. The problems of its application for image analysis and recognition are formulated. The method is based on the adaptive decomposition of the original arrays in a functional basis from among classical algebraic systems of polynomials and functions (Jacobi, Chebyshev, Lagrange, Laguerre, and Gegenbauer polynomials, etc., having one and two variables), as well as spherical functions. This approach combines analytical and digital data-processing procedures and is in fact a universal combined technology for processing information arrays.

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来源期刊

PATTERN RECOGNITION AND IMAGE ANALYSIS Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

1.80

自引率

20.00%

发文量

期刊介绍： The purpose of the journal is to publish high-quality peer-reviewed scientific and technical materials that present the results of fundamental and applied scientific research in the field of image processing, recognition, analysis and understanding, pattern recognition, artificial intelligence, and related fields of theoretical and applied computer science and applied mathematics. The policy of the journal provides for the rapid publication of original scientific articles, analytical reviews, articles of the world''s leading scientists and specialists on the subject of the journal solicited by the editorial board, special thematic issues, proceedings of the world''s leading scientific conferences and seminars, as well as short reports containing new results of fundamental and applied research in the field of mathematical theory and methodology of image analysis, mathematical theory and methodology of image recognition, and mathematical foundations and methodology of artificial intelligence. The journal also publishes articles on the use of the apparatus and methods of the mathematical theory of image analysis and the mathematical theory of image recognition for the development of new information technologies and their supporting software and algorithmic complexes and systems for solving complex and particularly important applied problems. The main scientific areas are the mathematical theory of image analysis and the mathematical theory of pattern recognition. The journal also embraces the problems of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including artificial intelligence, bioinformatics, medical informatics, data mining, big data analysis, machine vision, data representation and modeling, data and knowledge extraction from images, machine learning, forecasting, machine graphics, databases, knowledge bases, medical and technical diagnostics, neural networks, specialized software, specialized computational architectures for information analysis and evaluation, linguistic, psychological, psychophysical, and physiological aspects of image analysis and pattern recognition, applied problems, and related problems. Articles can be submitted either in English or Russian. The English language is preferable. Pattern Recognition and Image Analysis is a hybrid journal that publishes mostly subscription articles that are free of charge for the authors, but also accepts Open Access articles with article processing charges. The journal is one of the top 10 global periodicals on image analysis and pattern recognition and is the only publication on this topic in the Russian Federation, Central and Eastern Europe.