Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
RCC, ISEC, IT, WBS |
2024-03-14 10:20 |
Osaka |
Osaka Univ. (Suita Campus) |
IT2023-111 ISEC2023-110 WBS2023-99 RCC2023-93 |
This paper deals with variable-length lossy source coding in which the criteria are a cumulant generating function of co... [more] |
IT2023-111 ISEC2023-110 WBS2023-99 RCC2023-93 pp.238-240 |
AP |
2023-10-20 14:45 |
Iwate |
Iwate University (Primary: On-site, Secondary: Online) |
On Improving DOA Estimation Performance of VESPA by Using Multiple Guiding Sensor Pairs Nobuyoshi Kikuma, Kenta Noda, Kunio Sakakibara, Yoshiki Sugimoto (NITech) AP2023-126 |
Virtual ESPRIT Algorithm (VESPA) is a method for estimating the directions of arrival (DOA) using higher-order statistic... [more] |
AP2023-126 pp.147-152 |
SIS |
2013-12-12 13:30 |
Tottori |
Torigin Bunka Kaikan (Tottori) |
A Study on High Order Cumulant-based Noise Frame Detection for Impact Noise Norihiro Mamizu, Naoto Sasaoka, Shingo Okumura, Yoshio Itoh (Tottori Univ.) SIS2013-36 |
In this paper, we propose noise detection based on 4th order cumulant for impact noise. The proposed method takes advant... [more] |
SIS2013-36 pp.53-57 |
SANE |
2013-05-24 14:55 |
Tokyo |
Kikai-Shinko-Kaikan Bldg. |
Radiometric Identification Technology and Its Application to the Automatic Identification Systems Takashi Iwamoto, Takafumi Nagano (Mitsubishi Electric) SANE2013-11 |
Radiometric identification of emitters has attracted an attention to prevent fraudulent devices from accessing wireless ... [more] |
SANE2013-11 pp.15-18 |
SP, EA, SIP |
2013-05-16 15:55 |
Okayama |
|
A study on adaptive algorithm based on 4th order cumulant for speech enhancement in impulsive noise environment Kazumasa Ono, Naoto Sasaoka, Yoshio Itoh (Tottori Univ.) EA2013-10 SIP2013-10 SP2013-10 |
This paper proposes a speech enhancement based on a linear predictor with 4th order cumulant adaptive algorithm to reduc... [more] |
EA2013-10 SIP2013-10 SP2013-10 pp.55-59 |
SIS |
2012-03-02 11:00 |
Tokyo |
Shibuya Satellite Class, Tokyo City Univ. |
A Study on Sudden Noise Reduction based on Backward Linear Prediction with Least Fourth Cumulant Algorithm Toru Itoh, Naoto Sasaoka, Kazumasa Ono, Yoshio Itoh (Tottori Univ.) SIS2011-71 |
In this paper, the speech enhancement based on a linear prediction (LP) with least fourth cumulant algorithm is proposed... [more] |
SIS2011-71 pp.101-105 |
SANE |
2011-12-16 11:35 |
Saitama |
Nippon Institute of Technology |
A parameter setting method of temporal decorrelation source separation for periodic signals Takeshi Amishima, Kazufumi Hirata (Mitsubishi Electric Corp.) SANE2011-131 |
(To be available after the conference date) [more] |
SANE2011-131 pp.25-29 |
SIS, IPSJ-AVM |
2011-09-22 14:05 |
Akita |
|
A Study on Speech Enhancement Using LPEF with Cost Function Based 4th Order Cumulant for Sudden Noise Toru Itoh, Naoto Sasaoka, Yoshio Itoh (Tottori Univ.) SIS2011-38 |
In this paper, the speech enhancement with a linear prediction error filter (LPEF) based on 4th order cumulant is propos... [more] |
SIS2011-38 pp.111-115 |
NC, MBE (Joint) |
2010-03-10 09:50 |
Tokyo |
Tamagawa University |
Method for probing nonlinear properties of brain mechanisms with psychophysical reverse correlation Osamu Watanabe (Muroran Inst. of Tech.) NC2009-118 |
Many physiological researches have utilized the reverse correlation technique to probe receptive field structures of neu... [more] |
NC2009-118 pp.179-184 |
SP |
2009-03-05 13:30 |
Tokyo |
Tokyo Univ. of Technology |
Formant estimation methods of speech in noisy environment Keisuke Takemura, Nobuhiro Miki (Future Univ. Hakodate.) SP2008-142 |
In speech spectral analysis method, there are methods based on second statistics and third statistics to improve robustn... [more] |
SP2008-142 pp.1-6 |
SANE |
2007-01-19 11:40 |
Nagasaki |
Nagasaki Prefectural Art Museum |
Separation Capability of Independent Component Analysis for Superimposed Sinusoidal Signals Tetsuo Kirimoto (Univ. of Kitakyushu), Takeshi Amishima, Atsushi Okamura (Melco) SANE2006-123 |
ICA (Independent Component Analysis) has a remarkable capability of separating superimposed signals of independent stoch... [more] |
SANE2006-123 pp.25-30 |