Hidemitsu Ogawa

According to our database, Hidemitsu Ogawa authored at least 46 papers between 1969 and 2009.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2009

What Can We See behind Sampling Theorems?

Hidemitsu Ogawa

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2009

2008

Optimal noise suppression: A geometric nature of pseudoframes for subspaces.

Shidong Li, Hidemitsu Ogawa

Adv. Comput. Math., 2008

2006

Modulated Hebb-Oja learning Rule-a method for principal subspace analysis.

Marko Jankovic, Hidemitsu Ogawa

IEEE Trans. Neural Networks, 2006

Constructing Kernel Functions for Binary Regression.

Masashi Sugiyama, Hidemitsu Ogawa

IEICE Trans. Inf. Syst., 2006

2005

Optimal Sampling Operator for Signal Restoration in the Presence of Signal Space and Observation Space Noises.

Aqeel Syed, Hidemitsu Ogawa

IEICE Trans. Inf. Syst., 2005

2004

Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.

Marko Jankovic, Hidemitsu Ogawa

Int. J. Neural Syst., 2004

Characterization and Implementation of Partial Projection Filter in the Presence of Signal Space Noise.

Aqeel Syed, Hidemitsu Ogawa

IEICE Trans. Inf. Syst., 2004

Partial Projection Filter for Signal Restoration in the Presence of Signal Space Noise.

Aqeel Syed, Hidemitsu Ogawa

IEICE Trans. Inf. Syst., 2004

2003

A New Modulated Hebbian Learning Rule - Biologically Plausible Method for Local Computation of a Principal Subspace.

Marko Jankovic, Hidemitsu Ogawa

Int. J. Neural Syst., 2003

Radial basis function classifier for fault diagnostics.

Ganka Petkova Kovacheva, Hidemitsu Ogawa

Proceedings of the 1st Intenational Symposium on Information and Communication Technologies, 2003

2002

A unified method for optimizing linear image restoration filters.

Masashi Sugiyama, Hidemitsu Ogawa

Signal Process., 2002

Optimally generalizing neural networks with the ability to recover from single stuck-at r faults.

Hidekazu Iwaki, Hidemitsu Ogawa, Akira Hirabayashi

Syst. Comput. Jpn., 2002

Optimal design of regularization term and regularization parameter by subspace information criterion.

Masashi Sugiyama, Hidemitsu Ogawa

Neural Networks, 2002

Theoretical and Experimental Evaluation of the Subspace Information Criterion.

Masashi Sugiyama, Hidemitsu Ogawa

Mach. Learn., 2002

2001

A family of projection learnings.

Akira Hirabayashi, Hidemitsu Ogawa

Syst. Comput. Jpn., 2001

Properties of incremental projection learning.

Masashi Sugiyama, Hidemitsu Ogawa

Neural Networks, 2001

Incremental projection learning for optimal generalization.

Masashi Sugiyama, Hidemitsu Ogawa

Neural Networks, 2001

Noise suppression in training examples for improving generalization capability.

Akiko Nakashima, Hidemitsu Ogawa

Neural Networks, 2001

Error correcting memorization learning for noisy training examples.

Akiko Nakashima, Akira Hirabayashi, Hidemitsu Ogawa

Neural Networks, 2001

Incremental Active Learning for Optimal Generalization.

Masashi Sugiyama, Hidemitsu Ogawa

Neural Comput., 2001

Subspace Information Criterion for Model Selection.

Masashi Sugiyama, Hidemitsu Ogawa

Neural Comput., 2001

2000

Incremental Active Learning with Bias Reduction.

Masashi Sugiyama, Hidemitsu Ogawa

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

A new information criterion for the selection of subspace models.

Masashi Sugiyama, Hidemitsu Ogawa

Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000

1999

RKHS-based functional analysis for exact incremental learning.

Sethu Vijayakumar, Hidemitsu Ogawa

Neurocomputing, 1999

Training Data Selection for Optimal Generalization in Trigonometric Polynomial Networks.

Masashi Sugiyama, Hidemitsu Ogawa

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

What can memorization learning do?

Akira Hirabayashi, Hidemitsu Ogawa

Proceedings of the International Joint Conference Neural Networks, 1999

1998

Relative Karhunen-Loeve transform method for pattern recognition.

Yukihiko Yamashita, Yasuyuki Ikeno, Hidemitsu Ogawa

Proceedings of the Fourteenth International Conference on Pattern Recognition, 1998

1996

Relative Karhunen-Loève transform.

Yukihiko Yamashita, Hidemitsu Ogawa

IEEE Trans. Signal Process., 1996

Admissibility of memorization learning with respect to projection learning in the presence of noise.

Akira Hirabayashi, Hidemitsu Ogawa

Proceedings of International Conference on Neural Networks (ICNN'96), 1996

1995

A unified theory of the family of projection filters for signal and image estimation.

Yuji Koide, Yukihiko Yamashita, Hidemitsu Ogawa

Syst. Comput. Jpn., 1995

Pattern recognition in the presence of noise.

D. Liu, Yukihiko Yamashita, Hidemitsu Ogawa

Pattern Recognit., 1995

A functional analytic approach to incremental learning in optimally generalizing neural networks.

Sethu Vijayakumar, Hidemitsu Ogawa

Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

1994

Methods for choosing a training set which prevents over-learning.

Kazutaka Yamasaki, Hidemitsu Ogawa

Syst. Comput. Jpn., 1994

Relative Karhunen-Loeve operator.

Yukihiko Yamashita, Hidemitsu Ogawa

Proceedings of the 12th IAPR International Conference on Pattern Recognition, 1994

1993

Mutual relations among optimum image restoration filters.

Yukihiko Yamashita, Hidemitsu Ogawa

Syst. Comput. Jpn., 1993

Optimum image restoration filters and generalized inverses of operators.

Yukihiko Yamashita, Hidemitsu Ogawa

Syst. Comput. Jpn., 1993

Optimum image restoration and topological invariance.

Yukihiko Yamashita, Hidemitsu Ogawa

Syst. Comput. Jpn., 1993

A theory of over-learning in the presence of noise.

Kazutaka Yamasaki, Hidemitsu Ogawa

Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993

1992

Image restoration by averaged projection filter.

Yukihiko Yamashita, Hidemitsu Ogawa

Syst. Comput. Jpn., 1992

Properties of averaged projection filter for image restoration.

Yukihiko Yamashita, Hidemitsu Ogawa

Syst. Comput. Jpn., 1992

Karhunen-Loeve Subspace.

Hidemitsu Ogawa

Proceedings of the 11th IAPR International Conference on Pattern Recognition, 1992

1989

Estimation of the Reciprocating Point of a Rigid Body Moving Periodically in a Two-Dimensional Space - An Iterative Method Using a Correspondence between the Forward Path and the Backward Path.

Toyohiko Hayashi, Hidemitsu Ogawa, Taizo Iijima

Syst. Comput. Jpn., 1989

A method of extracting a kinematically characteristic point from the 3-dimensional motion of a rigid body.

Toyohiko Hayashi, Hidemitsu Ogawa, Taizo Iijima

Syst. Comput. Jpn., 1989

1986

Parametric projection filter for image and signal restoration.

Erkki Oja, Hidemitsu Ogawa

IEEE Trans. Acoust. Speech Signal Process., 1986

A unified approach to generalized sampling theorems.

Hidemitsu Ogawa

Proceedings of the IEEE International Conference on Acoustics, 1986

1969

Optimum Spatial Filter and Uncertainty

Hidemitsu Ogawa, Yoshinori Isomichi

Inf. Control., February, 1969