Articles listed below give examples of ART-based systems being used outside the CNS department at Boston University.
| Categories |
Topics:
Machine Learning,
Models:
ART 3, |
| Author(s) |
Hu, D.W. |
Jia. P, |
Yin, J.S. |
Zhou, Z.T. |
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| Abstract |
Adaptive resonance theory (ART) demonstrates how the brain learns to recognize and categorize vast amounts of information by using top-down expectations and attentional focusing. ART 3, one member of the ART family, embeds ... |
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| Categories |
Topics:
Machine Learning,
Models:
Fuzzy ARTMAP, |
| Author(s) |
Georgiopoulos, M. |
AlDaraiseh, A. |
Anagnostopoulos, G. |
Kaylani, A. |
Mollaghasemi, M. |
Wu, A.S. |
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| Abstract |
This paper focuses on the evolution of Fuzzy ARTMAP neural network classifiers, using genetic algorithms, with the objective of improving generalization performance (classification accuracy of the ART network on unseen test ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Information Fusion,
Models:
ART 2 / Fuzzy ART, |
| Author(s) |
Balaguer, E. |
Lisboa, P.J.G. |
MartinGuerrero, J.D. |
Palomares, A. |
SoriaOlivas, E. |
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| Abstract |
This paper proposes a methodology to optimize the future accuracy of a collaborative recommender application in a citizen Web portal. There are four stages namely, user modeling, benchmarking of clustering algorithms, ... |
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| Categories |
Topics:
Machine Learning,
Models:
Fuzzy ARTMAP, |
| Author(s) |
Lerner, B. |
Vigdor, B. |
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| Abstract |
In this paper, we modify the fuzzy ARTMAP (FA), neural network (NN) using the Bayesian framework in order to improve its classification accuracy while simultaneously reduce its category proliferation. The proposed algorithm, ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Medical Diagnosis,
Models:
ART 1, |
| Author(s) |
Delb, W. |
Low, Y.F. |
Strauss, D.J. |
Trenado, C. |
CoronaStrauss, F.I. |
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| Abstract |
Large-scale neural correlates of the tinnitus decompensation have been identified by using wavelet phase stability criteria of single sweep sequences of auditory late responses (ALRs). The suggested measure provided an ... |
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| Categories |
Topics:
Machine Learning,
Models:
ARTMAP, |
| Author(s) |
David, V.K. |
Rajasekaran, S. |
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| Abstract |
Pattern recognition is an important aspect of a dominant technology such as machine intelligence. Domain specific fuzzy-neuro models particularly for the ?black box? implementation of pattern recognition applications have ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Industrial Control,
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| Author(s) |
Arkan, M. |
Babu, V.S. |
Bezdicek, J. |
Chung, D. |
Discenzo, F.M. |
Flek, O. |
Loparo, K.A. |
Perovic, D.K. |
Perovic, S. |
Ryba, J. |
Sladek, B. |
Tusla, P. |
Unsworth, P.J. |
Zevchek, J.K. |
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| Abstract |
Systems and methods are disclosed for controlling, diagnosing and prognosing the health of a motorized system. The systems may comprise a diagnostics system, a prognostic system and a controller, wherein the diagnostics ... |
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| Categories |
Topics:
Machine Learning,
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| Author(s) |
Buxton, P.M. |
Martin, E.M. |
Tabor, E.P. |
Zalzala, A.M.S. |
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| Abstract |
A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically identify a characteristic of a fabrication process for components based on test data for the ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Industrial Control,
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| Author(s) |
Harrison, G.A. |
Turischev, A. |
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| Abstract |
A neural network learns the operating modes of a system being monitored under normal operating conditions. Anomalies can be automatically detected and learned. A control command can be issued or an alert can be issued in ... |
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| Categories |
Topics:
Machine Learning,
Applications:
Human-Machine Interface,
Industrial Control,
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| Author(s) |
Dupray, D.J. |
Karr, C.L. |
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| Abstract |
A location system is disclosed for commercial wireless telecommunication infrastructures. The system is an end-to-end solution having one or more location centers for outputting requested locations of commercially available ... |
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