Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory. - Yoshifusa Ito (Neural Networks, 1991)

Approximation of functions on a compact set by finite sums of a sigmoid function without scaling. - Yoshifusa Ito (Neural Networks, 1991)

Approximation of continuous functions on Rd by linear combinations of shifted rotations of a sigmoid function with and without scaling. - Yoshifusa Ito (Neural Networks, 1992)

Extension of approximation capability of three layered neural networks to derivatives. - Yoshifusa Ito (ICNN, 1993)

Approximation Capability of Layered Neural Networks with Sigmoid Units on Two Layers. - Yoshifusa Ito (Neural Comput., 1994)

Nonlinearity creates linear independence. - Yoshifusa Ito (Adv. Comput. Math., 1996)

Cultures of neurons on micro-electrode array and control of their axon growth in hybrid retinal implant. - Yoshifusa Ito; Tohru Yagi; H. Kanda; S. Tanaka; M. Watanabe; Yoshiki Uchikawa (IJCNN, 1999)

Surface-Tracing Approximation by Basis Functions and Its Application to Neural Networks. - Yoshifusa Ito (IJCNN (4), 2000)

Bayesian decision theory on three layered neural networks. - Yoshifusa Ito; Cidambi Srinivasan (ESANN, 2001)

Approximation of Bayesian Discriminant Function by Neural Networks in Terms of Kullback-Leibler Information. - Yoshifusa Ito; Cidambi Srinivasan (ICANN, 2001)

A Weak Condition on Linear Independence of Unscaled Shifts of a Function and Finite Mappings by Neural Networks. - Yoshifusa Ito (ICANN, 2002)

Multicategory Bayesian Decision Using a Three-Layer Neural Network. - Yoshifusa Ito; Cidambi Srinivasan (ICANN, 2003)

Activation Functions Defined on Higher-Dimensional Spaces for Approximation on Compact Sets with and without Scaling. - Yoshifusa Ito (Neural Comput., 2003)

Bayesian Learning of Neural Networks Adapted to Changes of Prior Probabilities. - Yoshifusa Ito; Cidambi Srinivasan; Hiroyuki Izumi (ICANN (2), 2005)

Bayesian decision theory on three-layer neural networks. - Yoshifusa Ito; Cidambi Srinivasan (Neurocomputing, 2005)

Discriminant Analysis by a Neural Network with Mahalanobis Distance. - Yoshifusa Ito; Cidambi Srinivasan; Hiroyuki Izumi (ICANN (2), 2006)

Learning of Bayesian Discriminant Functions by a Layered Neural Network. - Yoshifusa Ito; Cidambi Srinivasan; Hiroyuki Izumi (ICONIP (1), 2007)

A Neural Network having Fewer Inner Constants to be Trained and Bayesian Decision. - Yoshifusa Ito; Crinivasan Srinivasan; Hiroyuki Izumi (IJCNN, 2007)

Multi-category Bayesian Decision by Neural Networks. - Yoshifusa Ito; Cidambi Srinivasan; Hiroyuki Izumi (ICANN (1), 2008)

Simultaneous Approximations of Polynomials and Derivatives and Their Applications to Neural Networks. - Yoshifusa Ito (Neural Comput., 2008)

Learning of Mahalanobis Discriminant Functions by a Neural Network. - Yoshifusa Ito; Hiroyuki Izumi; Cidambi Srinivasan (ICONIP (1), 2009)

Simultaneous Learning of Several Bayesian Discriminant Functions by a Neural Network with Additional Nodes. - Yoshifusa Ito; Hiroyuki Izumi; Cidambi Srinivasan (Aust. J. Intell. Inf. Process. Syst., 2010)

A New Algorithm for Learning Mahalanobis Discriminant Functions by a Neural Network. - Yoshifusa Ito; Hiroyuki Izumi; Cidambi Srinivasan (ICONIP (2), 2011)

Simultaneous learning of several Bayesian and Mahalanobis discriminant functions by a neural network with additional nodes. - Yoshifusa Ito; Hiroyuki Izumi; Cidambi Srinivasan (IJCNN, 2011)

Simultaneous Learning of Several Bayesian and Mahalanobis Discriminant Functions by a Neural Network with Memory Nodes. - Yoshifusa Ito; Hiroyuki Izumi; Cidambi Srinivasan (ICONIP (5), 2012)

Estimation of Hidden Markov Chains by a Neural Network. - Yoshifusa Ito; Hiroyuki Izumi; Cidambi Srinivasan (ICONIP (1), 2014)