Discovering hidden recurring patterns in observable behavioral processes is an important issue frequently faced by numerous advanced students and researchers across many research areas, including psychology, biology, sports, robotics, media, finance, and medicine. As generally, themany powerful methods included in statistical software packages were not developed for this kind of analysis, discovering such patterns has proven a particularly difficult task, due to a lack of a) adequate formalized models of the kinds of patterns to look for, b) corresponding detection algorithms and c) their implementation in available software. The research described in this book is based on the application of such pattern types, algorithms and software developed from the late seventies to the present in the context of research in collaboration with human and animal behavioral research teams at internationally leading universities in the US and Europe, thus testing the usefulness and validity of the pattern types, algorithms and software in numerous research areas. With the (scale independent statistical hierarchical and fractal-like) T-Pattern at its heart, a set of proposed pattern types, called the T-System, forms the basis for the search algorithms implemented as the software THEME (TM) (vs. 6), which is easily available in free educational and full commercial versions.
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Magnus S. Magnusson, PhD
Magnus S. Magnusson is the creator of the T-pattern model and analysis and the author of the THEMETM Behavior Research software. He currently serves as a Research Professor at the University of Iceland, and is the founder and director of its Human Behavior Laboratory. He has worked as an invited professor at the Psychological Laboratory of University René Descartes Paris V in the Sorbonne, where in 1995 a formal inter-university collaboration convention was initiated with the T-Pattern model and analysis as the common reference. It has now been signed by 24 universities in Europe, the U.S. and Mexico. Dr. Magnusson has authored and coauthored numerous papers and chapters in many areas of behavioral and neuroscience including research on humans, animals and neuronal networks in living brains. In 2015 the Journal of Neuroscience Methods published a comprehensive review of his T-Pattern Analysis (TPA) for the analysis of the real-time structure of behavior and interaction, and a paper presenting results of TPA of interactions in neuronal networks in the olfactory bulb. He has given many invited talks at conferences and universities across the world.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Discovering hidden recurring patterns in observable behavioral processes is an important issue frequently faced by numerous advanced students and researchers across many research areas, including psychology, biology, sports, robotics, media, finance, and medicine. As generally, themany powerful methods included in statistical software packages were not developed for this kind of analysis, discovering such patterns has proven a particularly difficult task, due to a lack of a) adequate formalized models of the kinds of patterns to look for, b) corresponding detection algorithms and c) their implementation in available software. The research described in this book is based on the application of such pattern types, algorithms and software developed from the late seventies to the present in the context of research in collaboration with human and animal behavioral research teams at internationally leading universities in the US and Europe, thus testing the usefulness and validity of the pattern types, algorithms and software in numerous research areas. With the (scale independent statistical hierarchical and fractal-like) T-Pattern at its heart, a set of proposed pattern types, called the T-System, forms the basis for the search algorithms implemented as the software THEME (TM) (vs. 6), which is easily available in free educational and full commercial versions. 352 pp. Englisch. N° de réf. du vendeur 9781493932481
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