• Title/Summary/Keyword: IFS (iterated function system)

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Efficient Image Transmission System Using IFS (IFS를 이용한 고효율 영상전송 시스템)

  • Kim, Sang Hyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.11
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    • pp.6810-6814
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    • 2014
  • The concept of IFS (Iterated Function System) was applied to compress and transmit image data efficiently. To compress the image data with IFS, self-similarity was used to search a similar block. To improve the coding performance for the iterated function system with natural images, the image will be formed of properly transformed parts of itself to minimize the coding error. The simulation results using the proposed IFS represent high PSNR performance and improved compression efficiency with the coefficient of a recursive function.

TOPOLOGICAL ENTROPY OF ONE DIMENSIONAL ITERATED FUNCTION SYSTEMS

  • Nia, Mehdi Fatehi;Moeinaddini, Fatemeh
    • Honam Mathematical Journal
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    • v.42 no.4
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    • pp.681-699
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    • 2020
  • In this paper, topological entropy of iterated function systems (IFS) on one dimensional spaces is considered. Estimation of an upper bound of topological entropy of piecewise monotone IFS is obtained by open covers. Then, we provide a way to calculate topological entropy of piecewise monotone IFS. In the following, some examples are given to illustrate our theoretical results. Finally, we have a discussion about the possible applications of these examples in various sciences.

ON ATTRACTORS OF TYPE 1 ITERATED FUNCTION SYSTEMS

  • JOSE MATHEW;SUNIL MATHEW;NICOLAE ADRIAN SECELEAN
    • Journal of applied mathematics & informatics
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    • v.42 no.3
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    • pp.583-605
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    • 2024
  • This paper discusses the properties of attractors of Type 1 IFS which construct self similar fractals on product spaces. General results like continuity theorem and Collage theorem for Type 1 IFS are established. An algebraic equivalent condition for the open set condition is studied to characterize the points outside a feasible open set. Connectedness properties of Type 1 IFS are mainly discussed. Equivalence condition for connectedness, arc wise connectedness and locally connectedness of a Type 1 IFS is established. A relation connecting separation properties and topological properties of Type 1 IFS attractors is studied using a generalized address system in product spaces. A construction of 3D fractal images is proposed as an application of the Type 1 IFS theory.

A Fast Fractal Image Decoding Using the Encoding Algorithm by the Limitation of Domain Searching Regions (정의역 탐색영역 제한 부호화 알고리듬을 이용한 고속 프랙탈 영상복원)

  • 정태일;강경원;권기룡;문광석;김문수
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.12a
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    • pp.125-128
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    • 2000
  • The conventional fractal decoding was required a vast amount computational complexity. Since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested to that each range block was classified to iterated and non-iterated regions. If IFS region is contractive, then it can be performed a fast decoding. In this paper, a searched region of the domain in the encoding is limited to the range region that is similar with the domain block, and IFS region is a minimum. So, it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

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엑셀과 Fantastic Fractals을 이용한 Iterated Function System

  • An, Dae-Yeong
    • Communications of Mathematical Education
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    • v.9
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    • pp.283-297
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    • 1999
  • 수학에서는 컴퓨터를 활용해야 하고, 사회생활에서는 수학을 활용해야 한다. 이런 의미에서 엑셀을 수업 시간에 활용하는 것이 필요하다. 수학II의 일차변환을 엑셀을 어떻게 활용할 수 있는 가를 제시한다. 일차변환의 응용으로서, 이동을 포함시킨 아핀변환을 이용하여 프랙탈을 생성하는 방법을 찾아본다. 프랙탈을 생성하기 위해서는 IFS(Iterated Function System)에 의해 수 만번의 합성변환을 필요하므로 소프트웨어가 필수적이다. 여기서는 Fanstic Fractals 프로그램을 이용하여 직관적으로 얻은 그림에서 변환 행렬의 값을 구하여, 엑셀에서 두 가지 방법으로 분석하였다.

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A Fast Fractal Image Decoding Using the Minimizing Method of Domain Region by the Limitation of Searching Regions (탐색영역 제한에 의한 정의역 최소화 기법을 이용한 고속 프랙탈 영상복원)

  • 정태일;강경원;문광석;권기룡;김문수
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.2
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    • pp.13-19
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    • 2001
  • The conventional fractal decoding was required a vast amount computational complexity, since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested that each range block was classified to iterated and non-iterated regions. Non-iterated regions is called data dependency region, and if data dependency region extended, IFS regions are contractive. In this paper, a searched region of the domain is limited to the range regions that is similar with the domain blocks, and the domain region is more overlapped. As a result, data dependency region has maximum region, that is IFS regions can be minimum region. The minimizing method of domain region is defined to minimum domain(MD) which is minimum IFS region. Using the minimizing method of domain region, there is not influence PSNR(peak signal-to-noise ratio). And it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

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A Propagation Control Method Using Codes In The Fractal Deformation (코드를 활용한 프랙탈 변형의 전파 제어 방법)

  • Han, Yeong-Deok
    • Journal of Korea Game Society
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    • v.16 no.1
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    • pp.119-128
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    • 2016
  • In this paper, we consider an improved deformation method of IFS(iterated function system) fractal using codes of fractal points. In the existing deformation methods, the intermediate results of position dependent partial deformation propagate randomly due to the randomly selected maps of iteration. Therefore, in many cases, the obtained results become somewhat monotonous feeling shapes. To improve these limitations, we propose a method in which the selection of maps are controlled by codes of fractal points. Applying this method, we can obtain interesting fractal deformation conforming with its fractal features. Also, we propose a simple method, incorporating state variables, that can be applied to deformation of some fractal features other than position coordinates.

ECG Data Compression Using Iterated Function System (반복 함수계(Iterated Function Systems)를 이용한 심전도 데이타 압축)

  • Jun, Young-Il;Lee, Soon-Hyouk;Lee, Gee-Yeon;Yoon, Young-Ro;Yoon, Hyung-Ro
    • Proceedings of the KOSOMBE Conference
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    • v.1994 no.05
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    • pp.43-48
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    • 1994
  • 본 논문은 반복 수축 변환의 프랙탈(fractal) 이론에 근거한 심전도 데이터 압축에 관한 연구이다. 심전도 데이터에 반복 함수계(Iterated Function System : IFS) 모델을 적용하여 신호 자체의 자기 유사성(self-similarity)을 반복 수축 변환으로 표현하고, 그 매개변수만을 저장한다. 재구성시는 변환 매개변수를 반복 적용하여 원래의 신호에 근사되어지는 값을 얻게 된다. 심전도 데이타는 부분적으로 자기 유사성을 갖는다고 보고, 부분 자기-유사 프랙탈 모델(piecewise self-affine fractal model)로 표현될 수 있다. 이 모델은 신호를 특정 구간들로 나누어 각 구간들에 대해 최적 프랙탈 보간(fractal interpolation)을 구하고 그 중 오차가 가장 작은 매개변수만을 추출하여 저장한다. 이 방법을 심전도 데이타에 적용한 결과 특정 압축율에 대해 아주 적은 재생오차 (percent root-mean-square difference : PRD)를 얻을 수 있었다.

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