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1.
The paper describes chaotic neural network improvements to enhance the quality of n-dimensional image clustering. New synchronization type—cluster fragmentary synchronization was found. To reveal fragmentary synchronization a new method is proposed. Benderskaya Elena Nikolaevna was born in 1969. She graduated from Automation and Computer Systems department of the St. Petersburg State Polytechnical University in 1993. In 1996 she received her candidate’s degree in the field of mathematical and computer modeling. Since 1996, she delivers lectures at the Faculty of computer science, SPbSPU. Her scientific interests include different aspects of artificial intelligence, namely, neural networks and adjacent fields (pattern recognition, fuzzy logic, evolution computations, and synergetics). She is the winner of the Informica 2006 All-Russian Grant Contest (FGU GNII ITT)—a contest between the leaders of scientific teams working in the field of telecommunication technology. Zhukova Sofya Vitalyevna was born in 1981. She graduated from Automation and Computer Systems department of St. Petersburg State Polytechnical University in 2004. In 2007, under E.N. Benderskaya’s supervision she defended her PhD thesis in the field of system analysis, control, and information processing (informatics). Since 2008 she holds the appointment of associate professor at the Graduate School of Management, St. Petersburg State University. Her scientific interests include control theory, internet technologies, self-organization theory, the theory of nonlinear systems, and the theory of neural networks. She was awarded a grant from the Government of the Russian Federation as a result of the All-Russia Contest of 2006–2007 for Postgraduates.  相似文献   

2.
The problem of designing a system for speaker verification under the condition that the pronunciation of a phrase is nonuniform in time is considered. The DTW algorithm is studied as a method for smoothing a sequence of speech characteristics in time for improvement of the quality of further processing and making decision about verification. Geppener Vladimir Vladimirovich. Born 1940. Graduated from the Leningrad Electrotechnical Institute in 1964. Received candidate’s degree (in Engineering) in 1969 and Doctoral degree (in Engineering) in 2000. Professor at the Chair of Mathematical Software and Computer Applications of the St. Petersburg Electrotechnical University. Scientific interests are connected with the use of methods of artificial intelligence in systems of signal processing. Author and coauthor of more than 150 scientific publications. Haidar Adel S. Born 1964. Graduated from the Khar’kov Polytechnical Institute in 1988. Since 1989 worked as a programmer at the Center of Statistical Investigations in Aden (Yemen) and as an assistant professor at the Aden University. In 2001–2004, post-graduate student at the St. Petersburg Electrotechnical University. Scientific interests: pattern recognition, speech technologies, and digital signal processing. Author of 10 papers on computer methods for speech recognition. Simonchik Konstantin K. Born 1983. Since 2000, a student of the Chair of Mathematical Software and Computer Applications of the St. Petersburg Electrotechnical University. Scientific interests: pattern recognition, speech technologies, and adaptive and recurrent filtering. Author of 3 papers on applications of digital signal processing.  相似文献   

3.
Empirical mode decomposition (EMD) has recently been pioneered by Huang as a fully data-driven technique aimed at decomposing nonstationary signals in a set of “Intrinsic mode functions” (IMFs, Empirical modes). We will report on the main theoretical aspects of EMD, its extensive possibilities, and various contemporary applications. We will pay attention to detrending; denoising; Hilbert-Huang time-frequency analysis; and a very perspective and actual scientific direction known as Data Mining, which involves such problems as segmentation, cluster-analysis (clustering), classification, etc. The text was submitted by the authors in English. Klionski Dmitrii Mikhailovich. Born 1986. Bachelor of Engineering and Technology in Telecommunications. Programming engineer. Work in the field of applied mathematics, programming 3 years. Member of Regional St. Petersburg Division of RAPRIA. Scientific interests: adaptive signal analysis, methods of digital spectral analysis, statistical signal processing, Matlab. Author of 15 publications in the field of image recognition and analysis. Geppener Vladimir Vladimirovich. Born 1949. Received Doctoral degree (in Technical Sciences) in 1996. Leading researcher, Public Corporation "Scientific Engineering Center of St. Petersburg Electrical Engineering University", Professor of St. Petersburg State Electrical Engineering University. Member of Regional St. Petersburg Division of RAPRIA. Work in the fields of applied mathematics, programming over 30 years. Scientific interests: wavelet analysis, speech recognition, hydroacoustics, methods of digital spectral analysis, Matlab. Author of more than 50 publications. Oreshko Nikolai Ivanovich. Received Candidate’s degree (in Technical Sciences) in 1980. Leading researcher, Public Corporation “Scientific Engineering Center of St. Petersburg Electrical Engineering University”. Work in the fields of applied mathematics, programming over 30 years. Scientific interests: wavelet analysis, statistics, methods of digital spectral analysis, Matlab. Author of more than 50 publications. Vasiljev Aleksandr Vladimirovich. Born 1950. Received Candidate’s degree (in Technical Sciences) in 1996. Head of Department, Public Corporation “Scientific Engineering Center of St. Petersburg Electrical Engineering University”. Work in the fields of applied mathematics, programming over 30 years. Scientific interests: wavelet analysis, speech recognition, hydroacoustics, methods of digital spectral analysis, Matlab. Author of more than 50 publications.  相似文献   

4.
An algorithm for detection of the QRS complexes in the fetal ECG in the course of delivery is presented. A set of digital filters with the subsequent threshold detection of the QRS complexes and clarification of the position of the reference point is used in the algorithm. A comparison of the amplitudes of the current detected complex and a typical complex and correlation methods are employed for decreasing the noise level. The algorithm quality is experimentally estimated. Anatolii P. Nemirko. Born 1943. Graduated from the Leningrad Electrotechnical Institute in 1967. Received candidate’s degree in 1974 and doctoral degree in 1985. Professor of the St. Petersburg Electrotechnical University LETI. Scientific interests: pattern recognition, computerized signal analysis, development of biomedical computer systems. Author of more than 180 papers and eight books. Board member of the International Association for Pattern Recognition, member of editorial board of Pattern Recognition and Image Analysis. Aleksandr N. Kalinichenko. Born 1954. Graduated from the Leningrad Electrotechnical Institute in 1977. Received candidate’s degree in 1979. Associate Professor of the St. Petersburg Electrotechnical University LETI. Scientific interests: algorithms and methods for computerized analysis of biomedical signals. Author of more than 80 papers and one monograph. Roman A. Shepoval’nikov. Born 1980. Graduated from the St. Petersburg Electrotechnical University LETI in 2003. PhD student of the St. Petersburg Electrotechnical University LETI. Scientific interests: digital processing of biomedical signals and pattern recognition.  相似文献   

5.
Classical models in a human-machine system for physiological and psychological research are reviewed. Actual experimental data in this realm of science for psychophysiology are given. Main logical conclusions that can be used to develop software suitable for physiological and psychological research are made. Sergei V. Ivanov. Born in 1972. Graduated from St. Petersburg State University of Electrical Engineering in 1997. Graduated from the extension courses for teachers held in St. Petersburg State University of Electrical Engineering in 2000. At present, he teaches at St. Petersburg State University of Electrical Engineering. Ivanov applied for his candidate’s degree (05.11.16, Information and Measuring Control Systems, Medicobiological and Ecological Research). He is a candidate master in chess and checkers and his area of expertise is the development of algorithms and software tools for medicobiological research and processing medicobiological data (mostly of psychophysiologic nature) from the point of the game theory and statistical decisions, copyright issues for algorithms and software. He is the author of 25 scientific works (several papers in peer reviewed journals and theses in proceedings of Russian and international conferences) and the owner of two software registration certificates and author of one innovation proposal. In 1998–2000, his scientific research was supported at the Motorola grants contest held in St. Petersburg State University of Electrical Engineering. Awarded the bonus prize and the third degree diploma from St. Petersburg and Lenenergo authorities at the “tElectricity in St. Petersburg: 110 Years of History” R&D works contest in 2002. Ivanov was awarded a letter of commendation from the St. Petersburg Chess Federation for the moral and scientific popularization of chess in St. Petersburg in 2004. He was also awarded his third degree diploma as the winner of the R&D works contest for young scientists of St. Petersburg State University of Electrical Engineering in 2005.  相似文献   

6.
A new fast algorithm for computing a type of discrete cosine transform applied to compute modified cosine transform is described. The number of arithmetic operations of the algorithm is estimated and interpreted. The computational scheme with substitution of variables is presented, and methods for optimizing the code for digital signal processors are proposed. Vasilii S. Shaptala. Born 1978. Graduated from St. Petersburg Bonch-Bruevich University for Telecommunications in 2000. Received his candidate’s degree in 2003. At present, he is a software engineer at ARC International R&D Center. Scientific interests: digital signal processing in telecommunication systems. Author of 15 publications. Mikhail V. Korman. Born 1974. Graduated from the Department of Mathematics and Mechanics of St. Petersburg State University in 1997. Attended his postgraduate courses at the same university in 1997–2000. At present, he is a director at ARC International R&D Center. Scientific interests: fast orthogonal transformations, information encoding, rate-distortion optimization (encoding error optimization), numerical methods. Author of 5 articles on methods of solving parabolic and hyperbolic equations numerically.  相似文献   

7.
A method to obtain a code representation of handwritten signatures is described and an algorithm for signature verification based on such representations is proposed. Results of tests to determine efficient methods of image compression for the purpose of signature verification are presented. Konstantin Alekseev. Born 1979. Received Master’s degree in engineering and technology (Radioengineering) in 2002. Currently post-graduate student at St. Petersburg State Electrotechnical University “LETI”, chair of television and video. Scientific interests: digital image processing and pattern recognition. Author of three papers. Svetlana Egorova. Born 1931. Graduated from St. Petersburg State Electrotechnical University “LETI” in 1955, received Candidates degree (Eng.) in 1965; since 1968 a senior lecturer at the chair of television and video, St. Petersburg State Electrotechnical University “LETI”. Scientific interests: optical and digital image processing and compression methods in signal processing. Author of 141 papers.  相似文献   

8.
It is widely accepted that interfaces between computers and users should differ to accommodate individual, or group, needs. One method of 'personalizing' an interface is to have the system form a limited model of the user and employ it to fashion the dialogue to his needs. Unfortunately, little is known about the effect of adaptation on the man-machine interface. Although obvious advantages accrue from 'personalized' interfaces, there are also obvious disadvantages to presenting users with a changing, adapting and perhaps apparently inconsistent interface. The goal of this work is to determine the viability of an adaptive interface through a human-factor pilot study of a simple, specially designed, interactive computer system. The system uses menu-driven selection to retrieve entries from a large ordered telephone directory. This simple task has several advantages: it is a realistic application area for interactive computers; plausible adaptive modelling methods exist and have been studied theoretically; and previous work has determined the best way to display the menus to users. The results of this empirical study support the use of adaptive user modelling. In the (admittedly highly constrained) example system, a computer interface can indeed adapt successfully to every user. Although it does not necessarily generalize to other user interfaces, the result supplies evidence to refute published objections to adaptive user modelling in general.  相似文献   

9.
Design, implementation and evaluation of an adaptive user interface   总被引:2,自引:0,他引:2  
C.G. Thomas 《Knowledge》1993,6(4):230-238
Software systems developed in recent years are becoming increasingly powerful, but in most cases they tend to abandon the user to deal with the complexity of the system alone. There is an immense need for systems with individual, context-sensitive support. The paper discusses the development of such a support system with special focus on the user interface. The extension of an existing and complex program. Excel, to an adaptive and customizable system is described. This extension is called Flexcel, and it has been implemented and evaluated.

The primary aim of this extension is to provide a convenient environment for adapting Excel's user interface to particular users and their current tasks. For example, it allows the user to define new menu for actions that are frequently needed and normally require a tedious dialog step. Flexcel also analyzes the user's interaction style and presents adaptation suggestions. A critique component supports the user in his/her problem solving and learning activities related to the adaptability of Flexcel's user interface.  相似文献   


10.
P. Sukaviriya 《Knowledge》1993,6(4):220-229
Research on adaptive interfaces in the past has lacked support from user interface tools which allow interfaces to be easily created and modified. Also, current user interface tools provide no support for user models which can collect task-oriented information about users. Developing an adaptive interface requires a user model and an adaptation strategy. It also, however, requires a user interface which can be adapted. The latter task is often time-consuming, especially in relation to more sophisticated user interfaces.

The paper presents a user interface design environment, UIDE, which has a different software infrastracture. Designers use high-level specifications to create a model of an application and links from the application to various interface components. The model is the heart of all the design and run-time support in UIDE, including automatic dialog sequencing and help generation. UIDE provides automatic support for collecting task-oriented information about users, by the use of its high-level specifications in its application model as a basic construct for a user model. Some examples of adaptive interfaces and adaptive help are presented that use the information that is collectable in UIDE.  相似文献   


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