Unifying Themes in Complex Systems VII

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Yan Zeng

<p>This dissertation contributes to the understanding of fundamental issues in the highly interdisciplinary field of colloidal science. Beyond colloid science, the system also serves as a model for studying interactions in biological matter. This work quantitatively investigated the scaling laws of the characteristic lengths of the structuring of colloidal dispersions and tested the generality of these laws, thereby explaining and resolving some long-standing contradictions in the literature. <br><br>It revealed the effect of confinement on the structuring, independently of specific properties of the confining interfaces. In addition, it resolved the influence of roughness and charge of the confining interfaces on the structuring, as well as providing a method to measure the effect of surface deformability on colloidal structuring.</p><p></p>

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Harry Kesten

This is the eighth volume (out of a projected ten) with papers which appeared during the "Stochastic Equations and Their Applications" year (1985-1986) at the Institute for Mathematics and its Applications at the University of Minnesota. This volume, which is directed towards researchers in applied mathematics, engineering, and physics, contains contributions by: M. Aizeman, R. Holley, M. Bramson, D. Griffeath, D.C. Brydges, J.T. Chayes, L. Chayes, J.T. Cox, R. Durrett, R.H. Schonmann, S. Goldstein, L. Gray, J.W. Halley, R. Holley, H. Kesten, T.M. Leggett, C.M. Newman, H.E. Stanley, D. Stauffer, and J.C. Wierman.

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Alan F. Murray

Applications of Neural Networks gives a detailed description of 13 practical applications of neural networks, selected because the tasks performed by the neural networks are real and significant. The contributions are from leading researchers in neural networks and, as a whole, provide a balanced coverage across a range of application areas and algorithms. The book is divided into three sections. Section A is an introduction to neural networks for nonspecialists. Section B looks at examples of applications using `Supervised Training'. Section C presents a number of examples of `Unsupervised Training'. For neural network enthusiasts and interested, open-minded sceptics. The book leads the latter through the fundamentals into a convincing and varied series of neural success stories -- described carefully and honestly without over-claiming. Applications of Neural Networks is essential reading for all researchers and designers who are tasked with using neural networks in real life applications.

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Michel Remoissenet

Written for an interdisciplinary readership of physicists, engineers, and chemists, this book is a practical guide to the fascinating world of solitons. These waves of large amplitude propagate over long distances without dispersing and therefore show one of the most striking aspects of nonlinearity. The author addresses students, practitioners, and researchers, approaching the subject from the standpoint of applications in optics, hydrodynamics, and electrical and chemical engineering. The book also encourages the readers to perform their own experiments. Since the printing of the second edition of this book, there has been a large growth in the literature on nonlinear waves and so has the wide applicability of the subject to the physical, chemical and biological sciences. Accordingly, this third edition has been thoroughly revised. Some of the topics are brought up to date with pertinent references. Furthermore, the book now includes a completely new chapter on solitary waves in diffuse systems.