Hamada Nozomu | The Faculty Of Science And Tech Nology Keio University
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概要
関連著者
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Hamada Nozomu
The Faculty Of Science And Tech Nology Keio University
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HAMADA Nozomu
the Faculty of Science and Technology, Keio University
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Hamada Nozomu
The Faculty Of Science And Technology Keio University
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Wu Shengli
The Faculty Of Science And Tech Nology Keio University
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仲地 孝之
Faculty Of Science And Technology Keio University
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NAKACHI Takayuki
the Faculty of Science and Technology, Keio University
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YAMASHITA Katsumi
the Faculty of Engineering, University of the Ryukyus
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Wu Shengli
The Faculty Of Science And Technology Keio University
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Nakachi Takayuki
The Faculty Of Engineering University Of The Ryukyus
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YAMAOKA Tateo
The Faculty of Science and Technology, Keio University
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Yamashita K
Univ. Ryukyus
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Yamaoka Tateo
The Faculty Of Science And Technology Keio University
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SHINMURA Hideyuki
the Faculty of Science and Tech nology, Keio University
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KONDO Katsuya
Graduate School of Engineering, University of Hyogo
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浜田 望
慶應義塾大学理工学研究科総合デザイン工学専攻
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Nakachi Takayuki
Ntt Optical Network Systems Laboratories
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Shinmura Hideyuki
The Faculty Of Science And Tech Nology Keio University
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Taguchi A
Musashi Inst. Technol. Tokyo Jpn
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Kondo K
Graduate School Of Engineering University Of Hyogo
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Kondo K
The Faculty Of Science And Technology Keio University
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Akiyama T
Keio Univ. Kanagawa Jpn
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Nakachi T
Ntt Network Innovation Lab. Yokosuka‐shi Jpn
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MUIKAICHI Masahiro
the Faculty of Science and Technology Keio University
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KONDO Katsuya
the Faculty of Science and Technology Keio University
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Meguro Mitsuhiko
The Faculty Of Science And Technology Keio University:(present Address) The University Of Electro-co
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AKIYAMA Takashi
the Faculty of Science and Technology, Keio University
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Taguchi Akira
The Faculty Of Engineering Musashi Institute Of Technology
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Yamaoka T
Keio Univ. Yokohama‐shi Jpn
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Akiyama Takashi
The Faculty Of Science And Technology Keio University
著作論文
- Two-Dimensional Least Squares Lattice Algorithm for Linear Prediction
- An Extended Lattice Model of Two-Dimensional Autoregressive Fields
- Object Extraction from a Moving Background Using Velocity Estimation and Optimal Filter in the MixeD
- An Appropriate Spatial FrequencySelection Method for Moving Object Velocity Estimation in the MIxed Domain
- Design of Nonlinear Cellular Neural Network Filters for Detecting Linear Trajectory Signals
- Two Types of Adaptive Beamformer Using 2-D Joint Process Lattice Estimator
- 2-D Direction-of-Arrival Estimation Using a Linear Interpolation Technique for Circular Array
- Data-Dependent Weighted Median Filtering with Robust Motion Information for Restoring Image Sequence Degraded by Additive Gaussian and Impulsive Noise (Special Section on Noise Cancellation and Reduction Techniques)
- A Robust Velocity Estimation Method by Using Mixed Domain Phase Signal