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Your search keyword '"Berryman, Matthew John"' showing total 3 results
Start Over Author "Berryman, Matthew John" Topic artificial intelligence
3 results on '"Berryman, Matthew John"'

1. STATISTICAL TECHNIQUES FOR TEXT CLASSIFICATION BASED ON WORD RECURRENCE INTERVALS

Author

Andrew Allison, Matthew J. Berryman, Derek Abbott, Berryman, Matthew John, Allison, Andrew, and Abbott, D

Subjects
business.industry, Computer science, Applied Mathematics, General Mathematics, Stylography, text authorship, statistics of text, keyword extraction, Keyword extraction, General Physics and Astronomy, Interval (mathematics), computer.software_genre, Set (abstract data type), Statistical analysis, Artificial intelligence, business, computer, Natural language processing, Word (computer architecture), Hebrews
Abstract

We present a method for characterizing text based on a statistical analysis of word recurrence interval. This method can be used for extracting keywords from text, and also for comparing texts by an unknown author against a set of known authors. We also use these methods to comment on the controversial question of who wrote the letter to the Hebrews in the New Testament.

Published
2003
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2. Techniques for noise removal from EEG, EOG and air flow signals in sleep patients

Author

Matthew J. Berryman, Sheila R. Messer, Derek Abbott, Andrew Allison, Berryman, Matthew John, Messer, Sheila, Allison, Andrew, and Abbott, Derek

Subjects
air flow, medicine.diagnostic_test, business.industry, Computer science, Airflow, Shot noise, FOS: Physical sciences, Electroencephalography, Signal, blind source signal separation, EOG, Noise, Physics - Data Analysis, Statistics and Probability, medicine, Computer vision, Artificial intelligence, Sleep (system call), EEG, sleep, business, Noise removal, Data Analysis, Statistics and Probability (physics.data-an), Electronic circuit
Abstract

Noise is present in the wide variety of signals obtained from sleep patients. This noise comes from a number of sources, from presence of extraneous signals to adjustments in signal amplification and shot noise in the circuits used for data collection. The noise needs to be removed in order to maximize the information gained about the patient using both manual and automatic analysis of the signals. Here we evaluate a number of new techniques for removal of that noise, and the associated problem of separating the original signal sources., Comment: 9 pages, 3 figures

Published
2004
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3. Adaptive battle agents: Emergence in artificial life combat models

Author

SPIE: Smart Structures, Devices and Systems Sydney, Australia 2004-12-12, Berryman, Matthew John, Lim, Kim, Mann, Isaac, Santos, Ricardo, Tobin, Brad, Ryan, Alex, and Abbott, Derek

Subjects
emergent behaviour, agent-based modelling, artificial intelligence, Information Systems, complex adaptive systems, genetic algorithms
Published
2004

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