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[Keyword] iterated function systems(4hit)

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  • Posterior Matching for Gaussian Broadcast Channels with Feedback

    Lan V. TRUONG  Hirosuke YAMAMOTO  

     
    PAPER-Information Theory

      Vol:
    E100-A No:5
      Page(s):
    1165-1178

    In this paper, the posterior matching scheme proposed by Shayevits and Feder is extended to the Gaussian broadcast channel with feedback, and the error probabilities and achievable rate region are derived for this coding strategy by using the iterated random function theory. A variant of the Ozarow-Leung code for the general two-user broadcast channel with feedback can be realized as a special case of our coding scheme. Furthermore, for the symmetric Gaussian broadcast channel with feedback, our coding scheme achieves the linear-feedback sum-capacity like the LQG code and outperforms the Kramer code.

  • Cyclic D/A Converters Based on Iterated Function Systems

    Junya SHIMAKAWA  Toshimichi SAITO  

     
    LETTER-Nonlinear Problems

      Vol:
    E87-A No:10
      Page(s):
    2811-2814

    This letter considers relationship between cyclic digital-to-analog converters (DACs) and iterated function systems (IFSs). We introduce the cyclic DACs as inverse systems of analog-to-digital converters in terms of one-dimensional maps. We then compare the DACs with a typical example of existing applications of IFSs: chaos game representation for analysis of DNA structures. We also present a simple test circuit of a DAC for Gray decoding based on switched capacitors and confirm the basic operation experimentally.

  • Analysis of Scaling-Factor-Quantization Error in Fractal Image Coding

    Choong Ho LEE  Masayuki KAWAMATA  Tatsuo HIGUCHI  

     
    PAPER-Digital Signal Processing

      Vol:
    E80-A No:12
      Page(s):
    2572-2580

    This paper proposes an analysis method of scaling-factor-quantization error in fractal image coding using a state-space approach with the statistical analysis method. It is shown that the statistical analysis method is appropriate and leads to a simple result, whereas the deterministic analysis method is not appropriate and leads to a complex result for the analysis of fractal image coding. We derive the output error variance matrix for the measure of error and define the output error variance by scalar quantity as the mean of diagonal elements of the output error variance matrix. Examples are given to show that the scaling-factor-quantization error due to iterative computation with finite-wordlength scaling factors degrades the quality of decoded images. A quantitative comparison of experimental scaling-factor-quantization error with analytical result is made for the output error variance. The result shows that our analysis method is valid for the fractal image coding.

  • State-Space Approach to Roundoff Error Analysis of Fractal Image Coding

    Choong Ho LEE  Masayuki KAWAMATA  Tatsuo HIGUCHI  

     
    PAPER-Digital Signal Processing

      Vol:
    E80-A No:1
      Page(s):
    159-165

    Roundoff error due to iterative computation with finite wordlength degrades the quality of decoded images in fractal image coding that employs a deterministic iterated function system. This paper presents a state-space approach to roundoff error analysis of fractal image coding for grey-scale images. The output noise variance matrix and the noise matrix are derived for the measures of error and the output noise variance is newly defined as the pixel mean of diagonal elements of the output noise matrix. A quantitative comparison of experimental roundoff error with analytical result is made for the output noise variance. The result shows that our analysis method is valid for the fractal image coding. Our analysis method is useful to design a real-time and low-cost decoding hardware with finite wordlength for fractal image coding.