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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 41 - 60 of 71 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
EE 2012-01-26
10:20
Nagasaki   Dynamic characteristics model of Bi-Directional DC-DC Converter using state-space-averaging method
Sihun Yang, Kenta Goto, Junpei Mutsuro, Masahito Shoyama (Kyushu Univ.) EE2011-46
In the field of use of clean energy such as EV, wind power generation and solar power generation, the bi-directional DC-... [more] EE2011-46
pp.87-90
PRMU, FM 2011-12-16
16:30
Shizuoka Hamamatsu Campus, Shizuoka Univ. Nonparametric Bayesian State Estimation by Detecting Change Points and Sharing Segments on Time Series Data
Masamichi Shimosaka, Yuichi Moriya, Rui Fukui, Tomomasa Sato (Univ. of Tokyo) PRMU2011-145
In this paper, we propose a novel framework for estimating state spaces where the size is unknown. The proposed framewor... [more] PRMU2011-145
pp.119-124
IBISML 2011-11-09
15:45
Nara Nara Womens Univ. Inferring the time-varying input signals and the hidden states from the membrane potential of a neuron
Ryota Kobayashi (Ritsumeikan Univ.), Petr Lansky (Acad. of Sci. of the Czech), Shigeru Shinomoto (Kyoto Univ.) IBISML2011-52
We consider an estimation problem of the time-varying input signals and the ion channel states from a voltage trace of a... [more] IBISML2011-52
pp.67-70
IBISML 2011-11-10
15:45
Nara Nara Womens Univ. Image Segmentation and Restoration using Switching State-Space Model and Variational Bayesian Method
Ryota Hasegawa (Kansai Univ.), Ken Takiyama, Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.) IBISML2011-67
We derive a deterministic algorithm that restores and segments image using switching state-space model and variational B... [more] IBISML2011-67
pp.169-174
NC 2011-07-25
14:10
Hyogo Graduate School of Engineering, Kobe University Belief Propagation for Slow Feature Analysis
Tomoki Sekiguchi (The Univ. of Tokyo), Toshiaki Omori, Masato Okada (The Univ. of Tokyo/RIKEN) NC2011-26
The slow feature analysis (SFA) is a data analysis method that extracts
slowly varying features from time series data. ... [more]
NC2011-26
pp.31-36
NC 2011-07-26
09:30
Hyogo Graduate School of Engineering, Kobe University Statistical estimation of non-uniform dendritic membrane properties
Toshiaki Omori (Univ. of Tokyo/RIKEN), Toru Aonishi (Tokyo Tech.), Masato Okada (Univ. of Tokyo/RIKEN) NC2011-32
We propose a statistical algorithm for extracting non-uniform dendritic membrane properties from partially observable no... [more] NC2011-32
pp.65-70
NC, IPSJ-BIO [detail] 2011-06-24
16:30
Okinawa 50th Anniversary Memorial Hall, University of the Ryukyus Solving POMDPs using Restricted Boltzmann Machines with Echo State Networks
Makoto Otsuka, Junichiro Yoshimoto, Stefan Elfwing, Kenji Doya (OIST) NC2011-19
A partially observable Markov decision process (POMDP) can be solved in a model-based way using explicit knowledge of th... [more] NC2011-19
pp.143-148
DC 2010-10-14
15:10
Tokyo Kikai-Shinko-Kaikan Bldg Accelerating State Reachability Analysis with a GPU
Yoshimitsu Nakada, Tatsuhiro Tsuchiya, Tohru Kikuno (Osaka Univ.) DC2010-22
Reachability analysis is the process of exploring the state space of a system under verification. This step is fundament... [more] DC2010-22
pp.25-29
CPSY, DC
(Joint)
2010-08-03
- 2010-08-05
Ishikawa Kanazawa Cultural Hall An approach to state space explosion in the LMNtal model checker
Masato Gocho, Kazunori Ueda (Waseda Univ.) DC2010-17
Model checking is an important technique for system verification based on exhaustive search, but large-scale model check... [more] DC2010-17
pp.19-24
NLP 2010-07-12
11:55
Ishikawa Ishikawa Prefectural Bunkyo Hall Analysis Using Space Embedded Equation in Moment Vector Space for High-dimensional Nonlinear System
Hideki Satoh (Future Univ. Hakodate) NLP2010-33
A space embedded equation (SEE) has been developed for expressing an arbitrary high-dimensional target system as a low-d... [more] NLP2010-33
pp.23-28
CAS, MSS, VLD, SIP 2010-06-22
15:35
Hokkaido Kitami Institute of Technology Pseudo-IIR Adaptive Array Based on Spatial State-Space Filtering
Sho Iwazaki, Koichi Ichige, Hiroyuki Arai (Yokohama Nat'l Univ.) CAS2010-30 VLD2010-40 SIP2010-51 CST2010-30
This paper presents a pseudo-IIR construction of adaptive array based on spatial state-space filtering. The proposed app... [more] CAS2010-30 VLD2010-40 SIP2010-51 CST2010-30
pp.169-173
NC, MBE
(Joint)
2010-03-09
13:45
Tokyo Tamagawa University On statistical inference of estimating fluorescent indicator and intracellular ionic concentrations on the basis of a self-organizing state-space model
Ryohei Iwahashi (Osaka Univ.), Takashi Tateno (Osaka Univ./JST) NC2009-94
For measuring concentration of free calcium ([Ca2+]i) inside living cells, indicator dyes including fura-2 are widely us... [more] NC2009-94
pp.39-44
NC, MBE
(Joint)
2010-03-09
14:35
Tokyo Tamagawa University Estimation of Intracellure Calcium Ion Dynamics by Particle Filter -- Application for Actual Physiological Experimental Data --
Takamasa Tsunoda (Tokyo Inst. of Tech.), Toshiaki Omori (Univ Tokyo/RIKEN), Hiroyoshi Miyakawa (TUPLS), Masato Okada (Univ Tokyo/RIKEN), Toru Aonishi (Tokyo Inst. of Tech./RIKEN) NC2009-96
Recently, some statistical methods for estimating Ca concentration from fluorescent signals of Ca indicator dyes have be... [more] NC2009-96
pp.51-56
IN, NS, CS
(Joint)
2009-09-10
10:50
Miyagi Tohoku University (Miyagi) Decomposition of Network Traffic by a state space model
Yasuhiro Amano, Kazuo Yana (Hosei Univ.) NS2009-62
This paper proposes a method of WAN traffic decomposition. A state space model is constructed for the incoming WAN traff... [more] NS2009-62
pp.13-17
EA 2009-03-27
10:30
Tokyo   Kalman Filter Based Robust Restoration Method with Colored Driving Source
Shunichi Kitahara, Nari Tanabe (Tokyo Univ. of Sci, Suwa.), Toshihiro Furukawa (Tokyo Univ. of Sci), Hideaki Matsue (Tokyo Univ. of Sci, Suwa.), Shigeo Tsujii (Inst. of Info Security) EA2008-136
This paper proposes a Kalman filter based robust restoration method with colored driving source for degraded images. The... [more] EA2008-136
pp.1-5
NC, MBE
(Joint)
2009-03-11
13:55
Tokyo Tamagawa Univ. Estimation of Intracellular Calcium Ion Concentration by Non-Linear State Space Modeling
Takamasa Tsunoda (Tokyo Inst. of Tech.), Toshiaki Omori (univ. of tokyo/RIKEN Brain Sci Inst.), Hiroyoshi Miyakawa (Tokyo Univ. of Phar and Life Sci.), Masato Okada (univ. of tokyo/RIKEN Brain Sci Inst.), Toru Aonishi (Tokyo Inst. of Tech./RIKEN Brain Sci Inst.) NC2008-107
The ionic dynamics depending on the nervous activity recently attracts attentions of many researchers due to the rapid p... [more] NC2008-107
pp.25-30
NC, MBE
(Joint)
2009-03-13
16:05
Tokyo Tamagawa Univ. Dynamic relational data analysis based on exponential family matrix factorization.
Kohei Hayashi (Nara Inst. of Sci and Tech.), Jun-ichiro Hirayama (Kyoto Univ.), Shin Ishii (Kyoto Univ./Nara Inst. of Sci and Tech.) NC2008-175
We propose a new probabilistic model to analyze time-varying relational data such as e-mail transaction profiles. Our mo... [more] NC2008-175
pp.423-428
NLP 2009-02-28
16:35
Kanagawa   Response Properties of Chaotic Neural Network Model to Memory Pattern Flagments
Toshiyuki Hamada, Jousuke Kuroiwa, Hisakazu Ogura, Tomohiro Odaka, Haruhiko Shirai (Univ of Fukui) NLP2008-149
In this paper, we investigate response properties to memory pattern fragments
in chaotic wandering states among three ... [more]
NLP2008-149
pp.101-106
NLP 2009-02-28
16:55
Kanagawa   Delay Feedback Control to Chaotic Neural Network Model
Kouta Teramoto, Jousuke Kuroiwa, Hisakazu Ogura, Tomohiro Odaka, Haruhiko Shirai (Univ of Fukui) NLP2008-150
In this paper, we investigate a delay feedback control to chaotic wandering states in chaotic neural network model. In m... [more] NLP2008-150
pp.107-111
SIP, RCS 2009-01-22
16:40
Kumamoto Kumamoto University [Invited Talk] Merger of Control and Signal Processing -- State-Space Approach --
Takao Hinamoto (Hiroshima Univ.) SIP2008-144 RCS2008-192
Modern control theory, digital control theory, and digital signal processing (DSP) have intersecting features from the t... [more] SIP2008-144 RCS2008-192
pp.119-124
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