Digital signal processing (course master's degree program, Moscow State University )

Материал из MachineLearning.

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(Новая: {{TOCright}} * '''Master degree program''', 1 year, autumn, department MMP ( ММП), * '''Lectures''' — Thursday, 4:20 pm, room 605 * '''Control''' — exam, 14 June, 9:00, roo...)
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== Description: ==
== Description: ==
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The main goal of this course is to expose students to the mathematical theory of signal analysis, and at the same time, to some of its many applications in the finance, geophysic, image understanding, bioinformatics, and etc.
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Course begins with a discussion of the analysis and representation of discrete-time signal systems, including discrete-time convolution, difference equations, the z-transform, and the discrete-time Fourier transform. The signal is meant an experimentally acquired or mathematically simulated function of spatial coordinates and time which is to be analyzed with the purpose of studying behavior of the respective distributed dynamical system.
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It was even Leonard Euler who marked that
 everything what happens in the world
 bears the sense of 
some minimum or maximum. The second part of course consider a wide class of signal analysis problems, which allow for treating them in unified terms of respective standard mathematical optimization problem for which there exist or can be created effective methods of solving. A signal is considered as a set of experimentally acquired values of a number of variables each of which is associated with respective node of an undirected adjacency graph that presents the fixed structure of the data set. The proposed theoretical approach is illustrated with its applications to the problems of segmentation, smoothing, fine texture analysis, matching of visual images, multi-alignment of long molecular sequences.
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Версия 16:19, 13 июня 2016

Содержание

  • Master degree program, 1 year, autumn, department MMP ( ММП),
  • Lectures — Thursday, 4:20 pm, room 605
  • Control — exam, 14 June, 9:00, room 637
  • InstructorKrasotkina O.
  • Office hours — Tuesday, Thursday, 11:00 am : 19:00 pm, or by appointment, room 532


Description:

The main goal of this course is to expose students to the mathematical theory of signal analysis, and at the same time, to some of its many applications in the finance, geophysic, image understanding, bioinformatics, and etc. Course begins with a discussion of the analysis and representation of discrete-time signal systems, including discrete-time convolution, difference equations, the z-transform, and the discrete-time Fourier transform. The signal is meant an experimentally acquired or mathematically simulated function of spatial coordinates and time which is to be analyzed with the purpose of studying behavior of the respective distributed dynamical system.

It was even Leonard Euler who marked that
 everything what happens in the world
 bears the sense of 
some minimum or maximum. The second part of course consider a wide class of signal analysis problems, which allow for treating them in unified terms of respective standard mathematical optimization problem for which there exist or can be created effective methods of solving. A signal is considered as a set of experimentally acquired values of a number of variables each of which is associated with respective node of an undirected adjacency graph that presents the fixed structure of the data set. The proposed theoretical approach is illustrated with its applications to the problems of segmentation, smoothing, fine texture analysis, matching of visual images, multi-alignment of long molecular sequences. .

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