理数情報教育系

Ryuichi Ashino

  (芦野 隆一)

Profile Information

Affiliation
Professor, Division of Math, Sciences, and Information Technology in Education, Osaka Kyoiku University
Degree
Master of Sciences(Osaka City University)
理学修士(大阪市立大学)
Doctor of Sciences(Kyoto University)
理学博士(京都大学)

Researcher number
80249490
J-GLOBAL ID
200901034094044146
researchmap Member ID
1000135629

External link

Papers

 168
  • Takeshi Mandai, Ryuichi Ashino, Akira Morimoto
    Trends in Mathematics, 703-713, Oct 31, 2023  
  • Ryuichi Ashino, Takeshi Mandai, Akira Morimoto
    Japan Journal of Industrial and Applied Mathematics, Apr 26, 2023  
  • Mawardi Bahri, Ryuichi Ashino
    INFORMATION, 24(2) 85-92, Jun, 2021  Peer-reviewed
  • Mawardi Bahri, Amir Kamal Amir, Ryuichi Ashino
    International Journal of Wavelets, Multiresolution and Information Processing, 19(6) 2150027-1-2150027-19, 2021  Peer-reviewed
    This paper deals with the linear canonical wavelet transform. It is a non-trivial generalization of the ordinary wavelet transform in the framework of the linear canonical transform. We first present a direct relationship between the linear canonical wavelet transform and ordinary wavelet transform. Based on the relation, we provide an alternative proof of the orthogonality relation for the linear canonical wavelet transform. Some of its essential properties are also studied in detail. Finally, we explicitly derive several versions of inequalities associated with the linear canonical wavelet transform.
  • Mawardi Bahri, Ryuichi Ashino
    Sensor Networks and Signal Processing Proceedings of the 2nd Sensor Networks and Signal Processing (SNSP 2019), 19-22, (176) 311-323, Jul 17, 2020  Peer-reviewed
    In our previous work, we established some basic poverties of the linear canonical transform and obtained alternative form of convolution and correlation theorems. In this paper, we study essential properties of the linear canonical transform (LCT). The properties are modifications of the classical Fourier transform properties. They are very need in applying LCT in signal processing. In addition, we formulate an inequality associated with the LCT, which is different from the uncertainty principle in literature.

Misc.

 16

Books and Other Publications

 16

Presentations

 5
  • Ryuichi Ashino
    ISAAC Congress, Aug 6, 2021, International Society for Analysis, Applications and Computation (ISAAC)  Invited
  • Ryuichi Ashino
    The 10th International Conference on Information, Mar 6, 2021, International Information Institute  Invited
  • Ryuichi Ashino
    日本応用数理学会, Mar 5, 2021, The Japan Society for Industrial and Applied Mathematics
    A direct relation between the Fourier transform and the fractional Fourier transform is studied. Some properties of the fractional Fourier transform are investigated using this relation. Several versions of uncertainty principles involving the fractional Fourier transform are presented.
  • Ryuichi Ashino
    The Third International Conference on Mathematical Characterization, Analysis and Applications of Complex Information (CMCAA 2020) Sept 11th - Sept 13th 2020, Beijing, China, Sep 13, 2020, Beijing Natural Science Foundation Beijing Key Lab on Mathematical Characterization, Analysis, and Applications of Complex Information.  Invited
    Provide a platform for researchers to present and discuss the latest developments and trends in theory and methods in dealing with complex information.
  • Mawardi Bahri, Ryuichi Ashino
    2019 International Conference on Machine Learning and Intelligent Systems (MLIS 2019), Nov 19, 2019, National Dong Hwa University  Invited
    The event is aimed at providing a platform for knowledge exchange of the most recent scientific and technological advances and to strengthen the links in the scientific community. The plenary session of MLIS 2019 will include Keynote Speeches, Invited Speeches, Poster Presentations and Oral Presentations.

Research Projects

 31

Media Coverage

 1