Andrew D. Back

Publication Activity (10 Years)

Years Active: 1991-2023
Publications (10 Years): 9

Top Topics

Information Theoretic

Statistical Information

Top Venues

IEEE J. Sel. Top. Signal Process.

IEEE Trans. Inf. Theory

Publications

Andrew D. Back, Janet Wiles
Estimation of Statistical Manifold Properties of Natural Sequences using Information Topology. SSP (2023)
Andrew D. Back, Janet Wiles
An Information Theoretic Approach to Symbolic Learning in Synthetic Languages. Entropy 24 (2) (2022)
Andrew D. Back, Janet Wiles
Estimating Sentence-like Structure in Synthetic Languages Using Information Topology. Entropy 24 (7) (2022)
Andrew D. Back, Janet Wiles
Entropy Estimation Using a Linguistic Zipf-Mandelbrot-Li Model for Natural Sequences. Entropy 23 (9) (2021)
Andrew D. Back, Daniel Angus, Janet Wiles
Transitive Entropy - A Rank Ordered Approach for Natural Sequences. IEEE J. Sel. Top. Signal Process. 14 (2) (2020)
Jessica Korte, Axel Bender, Guy Edward Gallasch, Janet Wiles, Andrew D. Back
A Plan for Developing an Auslan Communication Technologies Pipeline. ECCV Workshops (2) (2020)
Andrew D. Back, Daniel Angus, Janet Wiles
Determining the Number of Samples Required to Estimate Entropy in Natural Sequences. IEEE Trans. Inf. Theory 65 (7) (2019)
Andrew D. Back, Daniel Angus, Janet Wiles
Determining the Number of Samples Required to Estimate Entropy in Natural Sequences. CoRR (2018)
Daniel Angus, Yeyang Yu, Paul Vrbik, Andrew D. Back, Janet Wiles
PauseCode: Computational Conversation Timing Analysis. MA3HMI@ICMI (2018)
Thomas P. Trappenberg, Jie Ouyang, Andrew D. Back
Input Variable Selection: Mutual Information and Linear Mixing Measures. IEEE Trans. Knowl. Data Eng. 18 (1) (2006)
Andrew D. Back, Tianping Chen
Universal Approximation of Multiple Nonlinear Operators by Neural Networks. Neural Comput. 14 (11) (2002)
Andrew D. Back, Thomas P. Trappenberg
Selecting inputs for modeling using normalized higher order statistics and independent component analysis. IEEE Trans. Neural Networks 12 (3) (2001)
Nicolangelo Iannella, Andrew D. Back
A spiking neural network architecture for nonlinear function approximation. Neural Networks 14 (6-7) (2001)
Thomas P. Trappenberg, Andrew D. Back
A Classification Scheme for Applications with Ambiguous Data. IJCNN (6) (2000)
Andrew D. Back, Thomas P. Trappenberg
Input variable selection using independent component analysis. IJCNN (1999)
Andrew D. Back, Bill G. Horne, Ah Chung Tsoi, C. Lee Giles
Alternative discrete-time operators: an algorithm for optimal selection of parameters. IEEE Trans. Signal Process. 47 (9) (1999)
Andrew D. Back, Ah Chung Tsoi
A Low Sensitivity Recurrent Neural Network. Neural Comput. 10 (1) (1998)
Andrew D. Back, Andreas S. Weigend
What drives stock returns?-an independent component analysis. CIFEr (1998)
Andrew D. Back, Andreas S. Weigend
A First Application of Independent Component Analysis to Extracting Structure from Stock Returns. Int. J. Neural Syst. 8 (4) (1997)
Andrew D. Back, Andrzej Cichocki
Blind Source Separation and Deconvolution of Fast Sampled Signals. ICONIP (1) (1997)
Ah Chung Tsoi, Andrew D. Back
Discrete time recurrent neural network architectures: A unifying review. Neurocomputing 15 (3-4) (1997)
Andrew D. Back, Tianping Chen
Approximation of Hybrid Systems by Neural Networks. ICONIP (1) (1997)
Steve Lawrence, C. Lee Giles, Ah Chung Tsoi, Andrew D. Back
Face recognition: a convolutional neural-network approach. IEEE Trans. Neural Networks 8 (1) (1997)
Steve Lawrence, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles
On the distribution of performance from multiple neural-network trials. IEEE Trans. Neural Networks 8 (6) (1997)
Steve Lawrence, Ah Chung Tsoi, Andrew D. Back
The Gamma MLP for Speech Phoneme Recognition. NIPS (1995)
Andrew D. Back, Ah Chung Tsoi
A Comparison of Discrete-Time Operator Models and for Nonlinear System Identification. NIPS (1994)
Ah Chung Tsoi, Andrew D. Back
Locally recurrent globally feedforward networks: a critical review of architectures. IEEE Trans. Neural Networks 5 (2) (1994)
Andrew D. Back, Ah Chung Tsoi
A Simplified Gradient Algorithm for IIR Synapse Multilayer Perceptrons. Neural Comput. 5 (3) (1993)
Andrew D. Back, Ah Chung Tsoi
An Adaptive Lattice Architecture for Dynamic Multilayer Perceptrons. Neural Comput. 4 (6) (1992)
Andrew D. Back, Ah Chung Tsoi
FIR and IIR Synapses, a New Neural Network Architecture for Time Series Modeling. Neural Comput. 3 (3) (1991)