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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-25 09:20 |
Tokushima | Naruto University of Education | Nonlinear analysis of vocal fold polyp data using recurrence plots Takuro Hirose, Kota Shiozawa, Isao Tokuda (Ritsumeikan Univ.), Miwa Fukino (Panasonic Holdings Corporation), Yoshiharu Soeta, Masanori Shiro (AIST)  NLP2023-100 MICT2023-55 MBE2023-46 |
Vocal fold oscillations can be regarded as nonlinear dynamics. Under certain circumstances, e.g., voice pathology or sin... [more] | NLP2023-100 MICT2023-55 MBE2023-46 pp.82-85 |
| NLP | 2023-11-28 13:00 |
Okinawa | Nago city commerce and industry association | Recurrence quantification analysis on electroencephalographic (EEG) potentials of epileptic seizure Makoto Sekiguchi, Tohru Ikeguchi (TUS) NLP2023-63 |
In this report, we analyze the characteristics of electroencephalographic (EEG) potentials of healthy individuals and ep... [more] | NLP2023-63 pp.21-26 |
| NLP, MSS | 2023-03-15 11:20 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Spatiotemporal dynamics of intermittent combustion oscillations in a cylindrical combustor with an off-center installed coaxial injector Hirotaka Okamoto, Kazuki Kawano, Hiroshi Gotoda (TUS), Takeshi Shoji, Seiji Yoshida (JAXA) MSS2022-66 NLP2022-111 |
We conduct an experimental study on intermittent combustion instability in a cylindrical combustor with an off-center in... [more] | MSS2022-66 NLP2022-111 pp.21-24 |
| NC, NLP | 2023-01-28 10:40 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Study on minimal diagonal line length effect on recurrence quantification analysis. Nina Sviridova, Tohru Ikeguchi (TUS) NLP2022-83 NC2022-67 |
The recurrence plot visualizes the complex multidimensional system’s dynamics as a two-dimensional binary image. Applied... [more] | NLP2022-83 NC2022-67 pp.11-15 |
| NLP | 2022-11-24 14:15 |
Shiga | (Primary: On-site, Secondary: Online) |
Fast reconstruction of 3D chromosome structure based on an inverse transform of a recurrence plot Yoshito Hirata (U. Tsukuba) NLP2022-63 |
A recurrence plot was originally proposed as a two-dimensional tool for visualizing a time series (Eckmann et al., EPL 1... [more] | NLP2022-63 pp.31-34 |
| NLP | 2022-11-24 14:50 |
Shiga | (Primary: On-site, Secondary: Online) |
[Invited Talk]
Hierarchical recurrence plot analysis for music waveform and MIDI as marked point process Miwa Fukino (Panasonic Holdings) NLP2022-64 |
A method for using recurrence plots (RPs) for music analysis is introduced. When analyzing music waveform data, one song... [more] | NLP2022-64 p.35 |
| NLP | 2022-11-25 15:15 |
Shiga | (Primary: On-site, Secondary: Online) |
Towards Defining Minimal Time Series Length for Normalized Recurrence Quantification Analysis Nina Sviridova, Tohru Ikeguchi (TUS) NLP2022-78 |
Estimating the minimal required time series length is an important problem in many applied studies. In our previous stud... [more] | NLP2022-78 pp.97-102 |
| NC, NLP (Joint) |
2021-01-21 10:05 |
Online | Online | Extraction of Property for Nonlinear Time Series by Changing Density of Recurrence Plots Shiki Kanamaru, Nina Sviridova (TUS), Yutaka Shimada (Saitama Univ.), Tohru Ikeguchi (TUS) NLP2020-41 |
A recurrence plot is one of the most effective nonlinear time series analysis methods for qualitatively understanding a ... [more] | NLP2020-41 pp.7-12 |
| NLP, CAS | 2019-10-22 14:30 |
Gifu | Gifu Univ. | An Analysis on Input and Output Signals of Neural Systems by Interspike Interval Reconstruction and Recurrence Plots Tohru Ikeguchi (TUS) CAS2019-32 NLP2019-72 |
In this paper, we analyzed the relationship between input and output signals of neural systems with the interspike int... [more] | CAS2019-32 NLP2019-72 pp.43-48 |
| NLP | 2019-05-10 14:55 |
Oita | J:COM HoltoHALL OITA | Feature extraction of nonlinear time series signal by threshold variation of recurrence plot Shiki Kanamaru (TUS), Yutaka Shimada (Saitama Univ.), Tohru Ikeguchi (TUS) NLP2019-5 |
In this report, we propose a feature extraction method of nonlinear time series by threshold variation of the recurrence... [more] | NLP2019-5 pp.23-28 |
| NLP | 2019-05-10 15:20 |
Oita | J:COM HoltoHALL OITA | A Study on Reconstructing Common Inputs to Neurons using Superposed Recurrence Plots Ryota Nomura, Tohru Ikeguchi (Tokyo Univ. Science) NLP2019-6 |
In this paper, we proposed a method for reconstructing common input data to single neurons only from observed spike seq... [more] | NLP2019-6 pp.29-34 |
| NLP, NC (Joint) |
2019-01-23 11:20 |
Hokkaido | The Centennial Hall, Hokkaido Univ. | An analysis on chaotic marked point process using constrained random shuffled surrogate data Kohei Yamamoto (TUS), Yutaka Shimada (Saitama Univ.), Tohru Ikeguchi (TUS) NLP2018-101 |
Marked point process data refer to a time series of discrete events with additional information. For example, se... [more] |
NLP2018-101 pp.29-34 |
| HCS | 2017-03-15 13:50 |
Miyagi | Dynamics of Interaction in an Performance Art
-- Analysis of the Distance as a Hidden Dimension of Communication -- Daichi Shimizu, Takeshi Okada (UT) HCS2016-95 |
In the performing arts, including dance, theatre, and music, performers present their art through complicated interactio... [more] | HCS2016-95 pp.29-34 |
|
| NLP | 2015-07-22 10:00 |
Hokkaido | Bibai Onsen Yu-rinkan | Can Recurrence Plots visualize task period in noisy NIRS data? Masako Sugai, Masaharu Adachi (TDU) NLP2015-76 |
NIRS (Near infra-red spectroscopy) is a spectroscopic device with which the brain activity can be measured non-invasivel... [more] | NLP2015-76 pp.47-52 |
| NLP | 2013-12-07 09:50 |
Overseas | City University of Hong Kong | Three coupled biological oscillators constructed with the true slime mold and its timeseries analysis Takahiro Noguchi, Hiroki Okabe, Kyoji Honda, Makito Ishizaki, Kuniyasu Shimizu (Chiba Inst. of Tech.) NLP2013-124 |
In this study, we experimentally measure a oscillation pattern of body thickness of a true slime mold put into three cou... [more] | NLP2013-124 pp.59-64 |
| NLP | 2011-11-09 13:40 |
Okinawa | Miyako Island Marine Terminal | ISI characterristics of Chaotic Spiking Oscillators with two kinds of impulsive switchings Satoshi Imai, Kazuki Yotsuji, Toshimichi Saito (HU) NLP2011-99 |
This paper stadies characteristics of inter-spike intervals of chotic spiking oscillators with two kinds of impulsive sw... [more] | NLP2011-99 pp.43-48 |
| NLP | 2009-11-11 11:30 |
Kagoshima | Change-Point Detection Based on Recurrence Plots Koji Iwayama, Yoshito Hirata, Kazuyuki Aihara, Hideyuki Suzuki (Univ. of Tokyo.) NLP2009-87 |
Recently a lot of nonlinear time series analysis methods have been proposed. However, we cannot apply most of those meth... [more] | NLP2009-87 pp.31-34 |
|
| NLP | 2008-03-27 15:00 |
Hyogo | Analysis method of chaotic time series using measures of networks. Yutaka Shimada, Tohru Ikeguchi (Saitama Univ.) NLP2007-161 |
Complex phenomena are ubiquitous in the real world, for example, fluctuation of financial indices in a stock market, po... [more] |
NLP2007-161 pp.43-48 |
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| NLP | 2006-03-21 11:40 |
Tokyo | Hosei Univ.(Ichigaya Campus) | Evaluating progress of reinforcement learning using recurrence plots Tetsuya Takahashi, Masaharu Adachi (TDU) |
(To be available after the conference date) [more] | NLP2005-155 pp.25-30 |
| NLP | 2005-01-24 16:15 |
Kagawa | Kagawa Univ. | * Tetsuya Takahashi, Masaharu Adachi (Tokyo Denki Univ.) |
Reinforcement learning is a kind of learning systems which can deal with an unknown environment.In the reinforcement lea... [more] | NLP2004-95 pp.35-40 |
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