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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ITE-ME, ITE-IST, BioX, SIP, MI, IE [detail] | 2024-06-06 14:35 |
Niigata | Nigata University (Ekinan-Campus "TOKIMATE") | Out of date numerical algorithms such as DFT Fumihiko Ishiyama (NTT) |
(To be available after the conference date) [more] | |
| NLP | 2024-05-10 09:30 |
Kagawa | Kagawa Prefecture Social Welfare Center | Spectrogram of electromagnetic pulse from lightning cloud Fumihiko Ishiyama, Atsushi Nagao, Toshihisa Masuda, Masato Maruyama (NTT)  NLP2024-9 |
(To be available after the conference date) [more] | NLP2024-9 pp.43-48 |
| NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-24 10:30 |
Tokushima | Naruto University of Education | Estimation of Determinism for Imaging Photoplethysmogram Ayane Mine, Nina Sviridova (TCU) NLP2023-86 MICT2023-41 MBE2023-32 |
Photoplethysmography is a method of acquiring biological information by irradiating light onto the fingertip and measuri... [more] | NLP2023-86 MICT2023-41 MBE2023-32 pp.16-20 |
| QIT (2nd) |
2023-12-17 17:30 |
Okinawa | OIST (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Liouvillian spectral analysis for dynamics of open quantum systems via dynamic mode decomposition Yuzuru Kato (FUN), Hiroya Nakao (Tokyo Tech) |
Dynamic mode decomposition (DMD) is a data-driven method for the estimation, prediction, and control of complex dynamica... [more] | |
| NLP | 2023-11-28 11:15 |
Okinawa | Nago city commerce and industry association | Dynamics of Reservoir in Echo State Network Shion Yoshida, Tohru Ikeguchi (TUS) NLP2023-62 |
Reservoir computing is one of the frameworks for machine learning for fast and highly accurate analysis of time series a... [more] | NLP2023-62 pp.15-20 |
| 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 | 2023-03-16 10:20 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Calculation of Lyapunov Exponent for Imaging Photoplethysmogram Hirofumi Nakayama, Nina Sviridova, Tohru Ikeguchi (TUS) MSS2022-81 NLP2022-126 |
Photoplethysmogram is a biological signal of the cardiovascular system that measures changes in the amount of light refl... [more] | MSS2022-81 NLP2022-126 pp.95-99 |
| 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 | 2022-11-25 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 |
| IN, CCS (Joint) |
2022-08-05 10:30 |
Hokkaido | Hokkaido University(Centennial Hall) (Primary: On-site, Secondary: Online) |
Detecting causality for spike trains based on reconstructing dynamical system from inter-spike intervals Kazuya Sawada (TUS), Yutaka Shimada (Saitama Univ.), Tohru Ikeguchi (TUS) CCS2022-36 |
In this report, by modifying a nonlinear method of detecting causality, we propose a method of detecting causality for p... [more] | CCS2022-36 pp.48-53 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-19 09:00 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Noise analysis of nonlinearly coupled circuits through power line Fumihiko Ishiyama (NTT) SIP2022-1 BioX2022-1 IE2022-1 MI2022-1 |
We are investigating countermeasure technique against electro-magnetic noise. We applied our method to the analysis of e... [more] | SIP2022-1 BioX2022-1 IE2022-1 MI2022-1 pp.1-6 |
| 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 |
| MSS, NLP (Joint) |
2020-03-10 13:30 |
Aichi | (Cancelled but technical report was issued) |
Influence of Resolution of Time Series Data on Causality Detection Kazuya Sawada (TUS), Yutaka Shimada (Saitama Univ.), Tohru Ikeguchi (TUS) NLP2019-128 |
In this report, we investigated the influence of resolution of time series data on causality detection by Convergent C... [more] |
NLP2019-128 pp.89-94 |
| NLP, NC (Joint) |
2020-01-25 09:30 |
Okinawa | Miyakojima Marine Terminal | On univariate continuous multimodal analysis and discrete multimodal analysis (2) Hideo Kanemitsu, Konno Hideaki (Hokkaido Univ. of Edu.) NLP2019-101 |
The (continuous) multimodal function of continuous variables defined by the authors focuses on the minimum (local) value... [more] | NLP2019-101 pp.83-88 |
| NLP | 2019-05-10 13:50 |
Oita | J:COM HoltoHALL OITA | Structure estimation of a neural network using Inter-spike-interval Kazuya Sawada (TUS), Yutaka Shimada (Saitama Univ.), Ikeguchi Tohru (TUS) NLP2019-3 |
In this paper, we apply the causal estimation method of Convergent Cross Mapping to a mathematical model of neural netwo... [more] | NLP2019-3 pp.13-18 |
| 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, 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 |
| PRMU, SP | 2018-06-29 10:00 |
Nagano | Revisiting interference-free power spectral representations of periodic signals Hideki Kawahara (Wakayama Univ.), Masanori Morise (Univ. Yamanashi), Kanru Hua (Univ. Illinois) PRMU2018-29 SP2018-9 |
We propose two algorithms to calculate interference-free power spectra of periodic signals. This set of algorithms is ou... [more] | PRMU2018-29 SP2018-9 pp.41-46 |
|
| NLP | 2017-03-14 14:30 |
Aomori | Nebuta Museum Warasse | An numerical analysis of nonlinear dynamics in a 3 dimensional farm tractor Masahisa Watanabe, Kenshi Sakai (TUAT) NLP2016-113 |
Dynamics of agricultural tractor has nonlinearity such as Jump phenomenon. Jump phenomenon is pointed out to be one of t... [more] | NLP2016-113 pp.43-46 |
| SP, SIP, EA | 2017-03-01 15:55 |
Okinawa | Okinawa Industry Support Center | [Invited Talk]
Multikernel Adaptive Filtering: Signal Processing and Machine Learning Masahiro Yukawa (Keio Univ.) EA2016-113 SIP2016-168 SP2016-108 |
We present the multikernel adaptive filtering and introduce its recent advances. Multikernel adaptive filtering is a rec... [more] | EA2016-113 SIP2016-168 SP2016-108 pp.177-182 |
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