Neural Network Essentials 1 Draft: Pattern Recognition Chapter

[1]  Robert J. Marks,et al.  Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks , 1999 .

[2]  Nils J. Nilsson,et al.  The Mathematical Foundations of Learning Machines , 1990 .

[3]  R. Bracewell The Fourier Transform and Its Applications , 1966 .

[4]  Paul J. Werbos,et al.  The Roots of Backpropagation: From Ordered Derivatives to Neural Networks and Political Forecasting , 1994 .

[5]  David Marr,et al.  VISION A Computational Investigation into the Human Representation and Processing of Visual Information , 2009 .

[6]  Geoffrey E. Hinton,et al.  Learning representations by back-propagation errors, nature , 1986 .

[7]  Andrew S. Glassner Principles of digital image synthesis. Volume 1 , 1995 .

[8]  M.H. Hassoun,et al.  Fundamentals of Artificial Neural Networks , 1996, Proceedings of the IEEE.

[9]  Zoher Z. Karu,et al.  Signals and Systems Made Ridiculously Simple , 1995 .

[10]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[11]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[12]  Marvin Minsky,et al.  Perceptrons: An Introduction to Computational Geometry , 1969 .

[13]  S. W. Kuffler Neurons in the retina; organization, inhibition and excitation problems. , 1952, Cold Spring Harbor symposia on quantitative biology.

[14]  William E. Boyce,et al.  Elementary differential equations and boundary value problems - Fourth edition , 1986 .

[15]  D. Hubel Eye, brain, and vision , 1988 .

[16]  Paul J. Werbos Backpropagation: basics and new developments , 1998 .

[17]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.