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This introduction to probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. Topics covered include conditional expectations, stochastic processes, Langevin equations, and Markov chain Monte Carlo algorithms. The applications include data assimilation, prediction from partial data, spectral analysis and turbulence. A special feature is the systematic analysis of memory effects.
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This book explores the connection between algebraic structures in topology and computational methods for 3-dimensional electric and magnetic field computation. Although known since the 19th century, ...
Electrochemical Detection Techniques in the Applied Biosciences: Fermentation and Bioprocess Control, Hygiene and Environmental Science
This work, the main results of which were announced in (CFNT), focuses on a new geometric explicit construction of inertial manifolds from integral manifolds generated by some initial dimensional ...
An application of the techniques of dynamical systems and bifurcation theories to the study of nonlinear oscillations. Taking their cue from Poincare, the authors stress the geometrical and ...
Electrochemical Detection Techniques in the Applied Biosciences Vol. 2 : Fermentation and Bioprocess Control
Musculoskeletal Anatomy : A Text and Guide for Dissection for Students in the Allied Health Sciences
A two-part volume containing a comprehensive description of the theory of entire and meromorphic functions of one complex variable and its applications, and a detailed review of recent investigations ...
Elwick explores how the concept of compound individuality brought together life scientists working in pre-Darwinian London. Scientists conducting research in comparative anatomy, physiology, cellular ...
Mathematics in the Social & Life Sciences: Theories, Models & Methods

