Neural Networks: A Guided Tour

[1]  C. Lee Giles,et al.  Learning and Extracting Finite State Automata with Second-Order Recurrent Neural Networks , 1992, Neural Computation.

[2]  Geoffrey E. Hinton,et al.  Self-organizing neural network that discovers surfaces in random-dot stereograms , 1992, Nature.

[3]  Jürgen Schmidhuber,et al.  LSTM can Solve Hard Long Time Lag Problems , 1996, NIPS.

[4]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[5]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[6]  John Moody,et al.  Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.

[7]  Yoshua Bengio,et al.  Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.

[8]  Paul J. Werbos,et al.  Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.

[9]  Van Paul Yee Regularized Radial Basis Function Networks: Theory and Applications to Probability Estimation, Classification, and Time Series Prediction , 1998 .

[10]  Tsung-Nan Lin,et al.  Remembering the past: the role of embedded memory in recurrent neural network architectures , 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.

[11]  Simon Haykin,et al.  A modular neural network for enhancement of cross-polar radar targets , 1996, Neural Networks.

[12]  D. Broomhead,et al.  Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks , 1988 .

[13]  Terence D. Sanger,et al.  An Optimality Principle for Unsupervised Learning , 1988, NIPS.

[14]  H. B. Barlow,et al.  Unsupervised Learning , 1989, Neural Computation.

[15]  Ralph Linsker,et al.  How to Generate Ordered Maps by Maximizing the Mutual Information between Input and Output Signals , 1989, Neural Computation.

[16]  Yoshua Bengio,et al.  Hierarchical Recurrent Neural Networks for Long-Term Dependencies , 1995, NIPS.

[17]  F. Girosi,et al.  Networks for approximation and learning , 1990, Proc. IEEE.

[18]  Ralph Linsker,et al.  Towards an Organizing Principle for a Layered Perceptual Network , 1987, NIPS.

[19]  Ronald J. Williams,et al.  A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.

[20]  E. Oja Simplified neuron model as a principal component analyzer , 1982, Journal of mathematical biology.

[21]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[22]  G. V. Puskorius,et al.  A signal processing framework based on dynamic neural networks with application to problems in adaptation, filtering, and classification , 1998, Proc. IEEE.

[23]  P. Werbos,et al.  Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .