Andrew D. Back

According to our database, Andrew D. Back authored at least 32 papers between 1991 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Estimation of Statistical Manifold Properties of Natural Sequences using Information Topology.

Andrew D. Back, Janet Wiles

Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

2022

Estimating Sentence-like Structure in Synthetic Languages Using Information Topology.

Andrew D. Back, Janet Wiles

Entropy, 2022

An Information Theoretic Approach to Symbolic Learning in Synthetic Languages.

Andrew D. Back, Janet Wiles

Entropy, 2022

2021

Entropy Estimation Using a Linguistic Zipf-Mandelbrot-Li Model for Natural Sequences.

Andrew D. Back, Janet Wiles

Entropy, 2021

2020

Transitive Entropy - A Rank Ordered Approach for Natural Sequences.

Andrew D. Back, Daniel Angus, Janet Wiles

IEEE J. Sel. Top. Signal Process., 2020

A Plan for Developing an Auslan Communication Technologies Pipeline.

Jessica Korte, Axel Bender, Guy Edward Gallasch, Janet Wiles, Andrew D. Back

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

2019

Determining the Number of Samples Required to Estimate Entropy in Natural Sequences.

Andrew D. Back, Daniel Angus, Janet Wiles

IEEE Trans. Inf. Theory, 2019

2018

PauseCode: Computational Conversation Timing Analysis.

Daniel Angus, Yeyang Yu, Paul Vrbik, Andrew D. Back, Janet Wiles

Proceedings of the 4th International Workshop on Multimodal Analyses Enabling Artificial Agents in Human-Machine Interaction, 2018

2012

Neural Network Classification and Prior Class Probabilities.

Steve Lawrence, Ian Burns, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles

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

2006

Input Variable Selection: Mutual Information and Linear Mixing Measures.

Thomas Trappenberg, Jie Ouyang, Andrew D. Back

IEEE Trans. Knowl. Data Eng., 2006

2002

Universal Approximation of Multiple Nonlinear Operators by Neural Networks.

Andrew D. Back, Tianping Chen

Neural Comput., 2002

2001

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

Andrew D. Back, Thomas Trappenberg

IEEE Trans. Neural Networks, 2001

A spiking neural network architecture for nonlinear function approximation.

Nicolangelo Iannella, Andrew D. Back

Neural Networks, 2001

2000

A Classification Scheme for Applications with Ambiguous Data.

Thomas Trappenberg, Andrew D. Back

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999

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

Andrew D. Back, Bill G. Horne, Ah Chung Tsoi, C. Lee Giles

IEEE Trans. Signal Process., 1999

Input variable selection using independent component analysis.

Andrew D. Back, Thomas Trappenberg

Proceedings of the International Joint Conference Neural Networks, 1999

1998

A Low Sensitivity Recurrent Neural Network.

Andrew D. Back, Ah Chung Tsoi

Neural Comput., 1998

What drives stock returns?-an independent component analysis.

Andrew D. Back, Andreas S. Weigend

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

1997

Face recognition: a convolutional neural-network approach.

Steve Lawrence, C. Lee Giles, Ah Chung Tsoi, Andrew D. Back

IEEE Trans. Neural Networks, 1997

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

Steve Lawrence, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles

IEEE Trans. Neural Networks, 1997

Discrete time recurrent neural network architectures: A unifying review.

Ah Chung Tsoi, Andrew D. Back

Neurocomputing, 1997

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

Andrew D. Back, Andreas S. Weigend

Int. J. Neural Syst., 1997

Blind Source Separation and Deconvolution of Fast Sampled Signals.

Andrew D. Back, Andrzej Cichocki

Proceedings of the Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, 1997

Approximation of Hybrid Systems by Neural Networks.

Andrew D. Back, Tianping Chen

Proceedings of the Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, 1997

1996

Neural Network Classification and Prior Class Probabilities.

Steve Lawrence, Ian Burns, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles

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

1995

The Gamma MLP for Speech Phoneme Recognition.

Steve Lawrence, Ah Chung Tsoi, Andrew D. Back

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

1994

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

Ah Chung Tsoi, Andrew D. Back

IEEE Trans. Neural Networks, 1994

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

Andrew D. Back, Ah Chung Tsoi

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

1993

A Simplified Gradient Algorithm for IIR Synapse Multilayer Perceptrons.

Andrew D. Back, Ah Chung Tsoi

Neural Comput., 1993

1992

New techniques for nonlinear system identification : a rapprochement between neural networks and linear systems / by Andrew D. Back

Andrew D. Back

PhD thesis, 1992

An Adaptive Lattice Architecture for Dynamic Multilayer Perceptrons.

Andrew D. Back, Ah Chung Tsoi

Neural Comput., 1992

1991

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

Andrew D. Back, Ah Chung Tsoi

Neural Comput., 1991