Estimation of Hidden Markov Chains by a Neural Network.

Yoshifusa Ito Yoshifusa Ito Hiroyuki Izumi Cidambi Srinivasan Estimation of Hidden Markov Chains by a Neural Network. 602-609 2014 ICONIP (1) https://doi.org/10.1007/978-3-319-12637-1_75 conf/iconip/2014-1 db/conf/iconip/iconip2014-1.html#ItoIS14 Yoshifusa Ito Hiroyuki Izumi Cidambi Srinivasan Simultaneous Learning of Several Bayesian and Mahalanobis Discriminant Functions by a Neural Network with Memory Nodes. 25-33 2012 ICONIP (5) https://doi.org/10.1007/978-3-642-34500-5_4 conf/iconip/2012-5 db/conf/iconip/iconip2012-5.html#ItoIS12 Yoshifusa Ito Hiroyuki Izumi Cidambi Srinivasan A New Algorithm for Learning Mahalanobis Discriminant Functions by a Neural Network. 596-605 2011 ICONIP (2) https://doi.org/10.1007/978-3-642-24958-7_69 conf/iconip/2011-2 db/conf/iconip/iconip2011-2.html#ItoIS11 Yoshifusa Ito Hiroyuki Izumi Cidambi Srinivasan Simultaneous learning of several Bayesian and Mahalanobis discriminant functions by a neural network with additional nodes. 733-740 2011 IJCNN https://doi.org/10.1109/IJCNN.2011.6033294 conf/ijcnn/2011 db/conf/ijcnn/ijcnn2011.html#ItoIS11

Yoshifusa Ito Hiroyuki Izumi Cidambi Srinivasan Simultaneous Learning of Several Bayesian Discriminant Functions by a Neural Network with Additional Nodes. 2010 11 Aust. J. Intell. Inf. Process. Syst. 4 http://cs.anu.edu.au/ojs/index.php/ajiips/article/view/1117 db/journals/ajiips/ajiips11.html#ItoIS10

Yoshifusa Ito Hiroyuki Izumi Cidambi Srinivasan Learning of Mahalanobis Discriminant Functions by a Neural Network. 417-424 2009 ICONIP (1) https://doi.org/10.1007/978-3-642-10677-4_47 conf/iconip/2009-3 db/conf/iconip/iconip2009-3.html#ItoIS09

Yoshifusa Ito Simultaneous Approximations of Polynomials and Derivatives and Their Applications to Neural Networks. 2757-2791 2008 20 Neural Comput. 11 https://doi.org/10.1162/neco.2008.03-07-494 https://www.wikidata.org/entity/Q51889253 db/journals/neco/neco20.html#Ito08

Yoshifusa Ito Cidambi Srinivasan Hiroyuki Izumi Multi-category Bayesian Decision by Neural Networks. 21-30 2008 ICANN (1) https://doi.org/10.1007/978-3-540-87536-9_3 conf/icann/2008-1 db/conf/icann/icann2008-1.html#ItoSI08 Yoshifusa Ito Cidambi Srinivasan Hiroyuki Izumi Learning of Bayesian Discriminant Functions by a Layered Neural Network. 238-247 2007 ICONIP (1) https://doi.org/10.1007/978-3-540-69158-7_26 conf/iconip/2007-1 db/conf/iconip/iconip2007-1.html#ItoSI07 Yoshifusa Ito Crinivasan Srinivasan Hiroyuki Izumi A Neural Network having Fewer Inner Constants to be Trained and Bayesian Decision. 2993-2998 2007 IJCNN https://doi.org/10.1109/IJCNN.2007.4371437 conf/ijcnn/2007 db/conf/ijcnn/ijcnn2007.html#ItoSI07 Yoshifusa Ito Cidambi Srinivasan Hiroyuki Izumi Discriminant Analysis by a Neural Network with Mahalanobis Distance. 350-360 2006 conf/icann/2006-2 ICANN (2) https://doi.org/10.1007/11840930_36 db/conf/icann/icann2006-2.html#ItoSI06

Yoshifusa Ito Cidambi Srinivasan Bayesian decision theory on three-layer neural networks. 209-228 2005 63 Neurocomputing https://doi.org/10.1016/j.neucom.2004.05.005 db/journals/ijon/ijon63.html#ItoS05

Yoshifusa Ito Cidambi Srinivasan Hiroyuki Izumi Bayesian Learning of Neural Networks Adapted to Changes of Prior Probabilities. 253-259 2005 conf/icann/2005-2 ICANN (2) https://doi.org/10.1007/11550907_40 db/conf/icann/icann2005-2.html#ItoSI05

Yoshifusa Ito Activation Functions Defined on Higher-Dimensional Spaces for Approximation on Compact Sets with and without Scaling. 2199-2226 2003 15 Neural Comput. 9 https://doi.org/10.1162/089976603322297359 db/journals/neco/neco15.html#Ito03

Yoshifusa Ito Cidambi Srinivasan Multicategory Bayesian Decision Using a Three-Layer Neural Network. 253-261 https://doi.org/10.1007/3-540-44989-2_31 2003 conf/icann/2003 ICANN db/conf/icann/icann2003.html#ItoS03 Yoshifusa Ito A Weak Condition on Linear Independence of Unscaled Shifts of a Function and Finite Mappings by Neural Networks. 337-343 2002 conf/icann/2002 ICANN https://doi.org/10.1007/3-540-46084-5_55 db/conf/icann/icann2002.html#Ito02 Yoshifusa Ito Cidambi Srinivasan Bayesian decision theory on three layered neural networks. 377-382 2001 conf/esann/2001 ESANN https://www.esann.org/sites/default/files/proceedings/legacy/es2001-7.pdf db/conf/esann/esann2001.html#ItoS01 Yoshifusa Ito Cidambi Srinivasan Approximation of Bayesian Discriminant Function by Neural Networks in Terms of Kullback-Leibler Information. 135-140 2001 conf/icann/2001 ICANN https://doi.org/10.1007/3-540-44668-0_19 db/conf/icann/icann2001.html#ItoS01 Yoshifusa Ito Surface-Tracing Approximation by Basis Functions and Its Application to Neural Networks. 227-231 2000 conf/ijcnn/2000-4 IJCNN (4) https://doi.org/10.1109/IJCNN.2000.860777 https://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.860777 db/conf/ijcnn/ijcnn2000-4.html#Ito00 Yoshifusa Ito Tohru Yagi H. Kanda S. Tanaka M. Watanabe Yoshiki Uchikawa Cultures of neurons on micro-electrode array and control of their axon growth in hybrid retinal implant. 178-181 1999 IJCNN https://doi.org/10.1109/IJCNN.1999.831480 conf/ijcnn/1999 db/conf/ijcnn/ijcnn1999.html#ItoYKTWU99

Yoshifusa Ito Nonlinearity creates linear independence. 189-203 1996 5 Adv. Comput. Math. 1 https://doi.org/10.1007/BF02124743 db/journals/adcm/adcm5.html#Ito96

Yoshifusa Ito Approximation Capability of Layered Neural Networks with Sigmoid Units on Two Layers. 1233-1243 1994 6 Neural Comput. 6 https://doi.org/10.1162/neco.1994.6.6.1233 db/journals/neco/neco6.html#Ito94

Yoshifusa Ito Extension of approximation capability of three layered neural networks to derivatives. 377-381 1993 ICNN https://doi.org/10.1109/ICNN.1993.298586 conf/icnn/1993 db/conf/icnn/icnn1993.html#Ito93

Yoshifusa Ito Approximation of continuous functions on R<sup>d</sup> by linear combinations of shifted rotations of a sigmoid function with and without scaling. 105-115 1992 5 Neural Networks 1 https://doi.org/10.1016/S0893-6080(05)80009-7 db/journals/nn/nn5.html#Ito92

Yoshifusa Ito Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory. 385-394 1991 4 Neural Networks 3 https://doi.org/10.1016/0893-6080(91)90075-G db/journals/nn/nn4.html#Ito91

Yoshifusa Ito Approximation of functions on a compact set by finite sums of a sigmoid function without scaling. 817-826 1991 4 Neural Networks 6 https://doi.org/10.1016/0893-6080(91)90060-I db/journals/nn/nn4.html#Ito91a

Hiroyuki Izumi H. Kanda Cidambi Srinivasan Crinivasan Srinivasan S. Tanaka Yoshiki Uchikawa M. Watanabe Tohru Yagi