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2020 – today
- 2023
[c10]Andrew D. Back, Janet Wiles
:
Estimation of Statistical Manifold Properties of Natural Sequences using Information Topology. SSP 2023: 542-546- 2022
- [j19]Andrew D. Back, Janet Wiles:
An Information Theoretic Approach to Symbolic Learning in Synthetic Languages. Entropy 24(2): 259 (2022) - [j18]Andrew D. Back, Janet Wiles:
Estimating Sentence-like Structure in Synthetic Languages Using Information Topology. Entropy 24(7): 859 (2022) - 2021
- [j17]Andrew D. Back, Janet Wiles:
Entropy Estimation Using a Linguistic Zipf-Mandelbrot-Li Model for Natural Sequences. Entropy 23(9): 1100 (2021) - 2020
- [j16]Andrew D. Back, Daniel Angus, Janet Wiles:
Transitive Entropy - A Rank Ordered Approach for Natural Sequences. IEEE J. Sel. Top. Signal Process. 14(2): 312-321 (2020) - [c9]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: 264-277
2010 – 2019
- 2019
- [j15]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): 4345-4352 (2019) - 2018
- [c8]Daniel Angus, Yeyang Yu, Paul Vrbik, Andrew D. Back, Janet Wiles:
PauseCode: Computational Conversation Timing Analysis. MA3HMI@ICMI 2018: 43-47 - [i1]Andrew D. Back, Daniel Angus, Janet Wiles:
Determining the Number of Samples Required to Estimate Entropy in Natural Sequences. CoRR abs/1805.08929 (2018) - 2012
- [p2]Steve Lawrence, Ian Burns, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles:
Neural Network Classification and Prior Class Probabilities. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 295-309
2000 – 2009
- 2006
- [j14]Thomas Trappenberg, Jie Ouyang, Andrew D. Back:
Input Variable Selection: Mutual Information and Linear Mixing Measures. IEEE Trans. Knowl. Data Eng. 18(1): 37-46 (2006) - 2002
- [j13]Andrew D. Back, Tianping Chen:
Universal Approximation of Multiple Nonlinear Operators by Neural Networks. Neural Comput. 14(11): 2561-2566 (2002) - 2001
- [j12]Nicolangelo Iannella, Andrew D. Back:
A spiking neural network architecture for nonlinear function approximation. Neural Networks 14(6-7): 933-939 (2001) - [j11]Andrew D. Back, Thomas Trappenberg:
Selecting inputs for modeling using normalized higher order statistics and independent component analysis. IEEE Trans. Neural Networks 12(3): 612-617 (2001) - 2000
- [c7]Thomas Trappenberg, Andrew D. Back:
A Classification Scheme for Applications with Ambiguous Data. IJCNN (6) 2000: 296-301
1990 – 1999
- 1999
- [j10]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): 2612-2615 (1999) - [c6]Andrew D. Back, Thomas Trappenberg:
Input variable selection using independent component analysis. IJCNN 1999: 989-992 - 1998
- [j9]Andrew D. Back, Ah Chung Tsoi:
A Low Sensitivity Recurrent Neural Network. Neural Comput. 10(1): 165-188 (1998) - [c5]Andrew D. Back, Andreas S. Weigend:
What drives stock returns?-an independent component analysis. CIFEr 1998: 141-156 - 1997
- [j8]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): 473-484 (1997) - [j7]Ah Chung Tsoi, Andrew D. Back:
Discrete time recurrent neural network architectures: A unifying review. Neurocomputing 15(3-4): 183-223 (1997) - [j6]Steve Lawrence, C. Lee Giles, Ah Chung Tsoi, Andrew D. Back:
Face recognition: a convolutional neural-network approach. IEEE Trans. Neural Networks 8(1): 98-113 (1997) - [j5]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): 1507-1517 (1997) - [c4]Andrew D. Back, Tianping Chen:
Approximation of Hybrid Systems by Neural Networks. ICONIP (1) 1997: 326-329 - [c3]Andrew D. Back, Andrzej Cichocki:
Blind Source Separation and Deconvolution of Fast Sampled Signals. ICONIP (1) 1997: 637-640 - 1996
- [p1]Steve Lawrence, Ian Burns, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles:
Neural Network Classification and Prior Class Probabilities. Neural Networks: Tricks of the Trade 1996: 299-313 - 1995
- [c2]Steve Lawrence, Ah Chung Tsoi, Andrew D. Back:
The Gamma MLP for Speech Phoneme Recognition. NIPS 1995: 785-791 - 1994
- [j4]Ah Chung Tsoi, Andrew D. Back:
Locally recurrent globally feedforward networks: a critical review of architectures. IEEE Trans. Neural Networks 5(2): 229-239 (1994) - [c1]Andrew D. Back, Ah Chung Tsoi:
A Comparison of Discrete-Time Operator Models and for Nonlinear System Identification. NIPS 1994: 883-890 - 1993
- [j3]Andrew D. Back, Ah Chung Tsoi:
A Simplified Gradient Algorithm for IIR Synapse Multilayer Perceptrons. Neural Comput. 5(3): 456-462 (1993) - 1992
- [b1]Andrew D. Back:
New techniques for nonlinear system identification : a rapprochement between neural networks and linear systems / by Andrew D. Back. University of Queensland, Australia, 1992 - [j2]Andrew D. Back, Ah Chung Tsoi:
An Adaptive Lattice Architecture for Dynamic Multilayer Perceptrons. Neural Comput. 4(6): 922-931 (1992) - 1991
- [j1]Andrew D. Back, Ah Chung Tsoi:
FIR and IIR Synapses, a New Neural Network Architecture for Time Series Modeling. Neural Comput. 3(3): 375-385 (1991)
Coauthor Index
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