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Lieferstatus:	i.d.R. innert 7-14 Tagen versandfertig
Veröffentlichung:	November 2013
Genre:	Naturwissensch., Medizin, Technik
	Applied Dynamical Systems / Artificial Intelligence / C / Complex systems / complexity / Computational complexity / Computational Intelligence / Computational Intelligence;Dynamic Systems / Computer architecture & logic design / Computer logic / Computer programming / software engineering / Cybernetics & systems theory / Dynamical systems / Dynamics & statics / engineering / Logics and Meanings of Programs / Statistical physics / Statistical Physics and Dynamical Systems / Theoretical, Mathematical and Computational Physics / Theory of Computation
ISBN:	9783642269387
EAN-Code:	9783642269387
Verlag:	Springer Berlin Heidelberg
Einband:	Kartoniert
Sprache:	English
Serie:	#371 - Studies in Computational Intelligence
Dimensionen:	H 235 mm / B 155 mm / D 12 mm
Gewicht:	330 gr
Seiten:	212
Zus. Info:	Paperback
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Dynamic logic (DL) recently had a highest impact on the development in several areas of modeling and algorithm design. The book discusses classical algorithms used for 30 to 50 years (where improvements are often measured by signal-to-clutter ratio), and also new areas, which did not previously exist. These achievements were recognized by National and International awards. Emerging areas include cognitive, emotional, intelligent systems, data mining, modeling of the mind, higher cognitive functions, evolution of languages and other. Classical areas include detection, recognition, tracking, fusion, prediction, inverse scattering, and financial prediction. All these classical areas are extended to using mixture models, which previously was considered unsolvable in most cases. Recent neuroimaging experiments proved that the brain-mind actually uses DL. "Emotional Cognitive Neural Algorithms with Engineering Applications" is written for professional scientists and engineers developing computer and information systems, for professors teaching modeling and algorithms, and for students working on Masters and Ph.D. degrees in these areas. The book will be of interest to psychologists and neuroscientists interested in mathematical models of the brain and min das well.