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Your search keyword '"Berryman, Matthew John"' showing total 4 results
Start Over Author "Berryman, Matthew John" Topic general physics and astronomy
4 results on '"Berryman, Matthew John"'

1. Scaling in small-world resistor networks

Author

Gyorgy Korniss, Kevin E. Bassler, Balazs Kozma, Derek Abbott, M. B. Hastings, Matthew J. Berryman, Korniss, G, Hastings, M, Bassler, M, Kozma, B, Berryman, Matthew John, and Abbott, Derek

Subjects
Physics, Statistical Mechanics (cond-mat.stat-mech), Process (computing), FOS: Physical sciences, General Physics and Astronomy, Conductance, Propagator, Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter Physics, 01 natural sciences, Standard deviation, 010305 fluids & plasmas, law.invention, Power (physics), law, 0103 physical sciences, Small-world model, Resistor networks, Scaling, Limit (mathematics), Statistical physics, Resistor, 010306 general physics, Condensed Matter - Statistical Mechanics
Abstract

We study the effective resistance of small-world resistor networks. Utilizing recent analytic results for the propagator of the Edwards-Wilkinson process on small-world networks, we obtain the asymptotic behavior of the disorder-averaged two-point resistance in the large system-size limit. We find that the small-world structure suppresses large network resistances: both the average resistance and its standard deviation approaches a finite value in the large system-size limit for any non-zero density of random links. We also consider a scenario where the link conductance decays as a power of the length of the random links, $l^{-\alpha}$. In this case we find that the average effective system resistance diverges for any non-zero value of $\alpha$., Comment: 15 pages, 6 figures

Published
2006
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2. 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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3. Review of signal processing in genetics

Author

Matthew J. Berryman, Derek Abbott, C. R. Wilkinson, Andrew Allison, Berryman, Matthew John, Allison, Andrew, Wilkinson, Chris, and Abbott, Derek

Subjects
Genetics, Signal processing, Sequence analysis, Computer science, General Mathematics, Applied Mathematics, Autocorrelation, General Physics and Astronomy, Spectral analysis, Field (computer science), DNA sequencing
Abstract

This paper reviews applications of signal processing techniques to a number of areas in the field of genetics. We focus on techniques for analyzing DNA sequences, and briefly discuss applications of signal processing to DNA sequencing, and other related areas in genetics that can provide biologically significant information to assist with sequence analysis.

Published
2005

4. Mutual information for examining correlations in DNA

Author

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

Subjects
Computer science, Applied Mathematics, General Mathematics, Measure (physics), Populations and Evolution (q-bio.PE), General Physics and Astronomy, Mutual information, computer.software_genre, DNA, correlations, mutual information, Fractal, FOS: Biological sciences, Statistics, Data mining, Quantitative Biology - Populations and Evolution, computer
Abstract

This paper examines two methods for finding whether long-range correlations exist in DNA: a fractal measure and a mutual information technique. We evaluate the performance and implications of these methods in detail. In particular we explore their use comparing DNA sequences from a variety of sources. Using software for performing in silico mutations, we also consider evolutionary events leading to long range correlations and analyse these correlations using the techniques presented. Comparisons are made between these virtual sequences, randomly generated sequences, and real sequences. We also explore correlations in chromosomes from different species., Comment: 8 pages, 3 figures

Published
2004
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