# Andrew D. Back

According to our database

^{1}, Andrew D. Back## Timeline

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## Bibliography

2012

Neural Network Classification and Prior Class Probabilities.

Proceedings of the Neural Networks: Tricks of the Trade - Second Edition, 2012

2006

Input Variable Selection: Mutual Information and Linear Mixing Measures.

IEEE Trans. Knowl. Data Eng., 2006

2002

Universal Approximation of Multiple Nonlinear Operators by Neural Networks.

Neural Computation, 2002

2001

Selecting inputs for modeling using normalized higher order statistics and independent component analysis.

IEEE Trans. Neural Networks, 2001

A spiking neural network architecture for nonlinear function approximation.

Neural Networks, 2001

2000

A Classification Scheme for Applications with Ambiguous Data.

IJCNN (6), 2000

1999

Alternative discrete-time operators: an algorithm for optimal selection of parameters.

IEEE Trans. Signal Processing, 1999

1998

A Low Sensitivity Recurrent Neural Network.

Neural Computation, 1998

What drives stock returns?-an independent component analysis.

Proceedings of the IEEE/IAFE/INFORMS 1998 Conference on Computational Intelligence for Financial Engineering, 1998

1997

Face recognition: a convolutional neural-network approach.

IEEE Trans. Neural Networks, 1997

On the distribution of performance from multiple neural-network trials.

IEEE Trans. Neural Networks, 1997

Discrete time recurrent neural network architectures: A unifying review.

Neurocomputing, 1997

A First Application of Independent Component Analysis to Extracting Structure from Stock Returns.

Int. J. Neural Syst., 1997

1996

Neural Network Classification and Prior Class Probabilities.

Proceedings of the Neural Networks: Tricks of the Trade, 1996

1995

The Gamma MLP for Speech Phoneme Recognition.

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

1994

Locally recurrent globally feedforward networks: a critical review of architectures.

IEEE Trans. Neural Networks, 1994

A Comparison of Discrete-Time Operator Models and for Nonlinear System Identification.

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1993

A Simplified Gradient Algorithm for IIR Synapse Multilayer Perceptrons.

Neural Computation, 1993

1992

An Adaptive Lattice Architecture for Dynamic Multilayer Perceptrons.

Neural Computation, 1992

1991

FIR and IIR Synapses, a New Neural Network Architecture for Time Series Modeling.

Neural Computation, 1991