This book provides a comprehensive review of the works in the rapidly evolving field of neural networks and brain studies. Its purpose is two-fold: to help physicists entering this field to get a broader view of the context of the domain, and to help scientists of other disciplines to reach a better understanding of the physicists' contributions within a context of perspectives they can relate to.Included in the volume are 68 carefully selected, high quality reprints to provide the volume with both breadth and depth. It is organized into 5 sections and 22 chapters, both the sections and chapters being preceded by introductory comments by the editors.
Computational physics is a rapidly growing subfield of computational science, in large part because computers can solve previously intractable problems or simulate natural processes that do not have analytic solutions. The next step beyond Landau's First Course in Scientific Computing and a follow-up to Landau and Páez's Computational Physics, this text presents a broad survey of key topics in computational physics for advanced undergraduates and beginning graduate students, including new discussions of visualization tools, wavelet analysis, molecular dynamics, and computational fluid dynamics. By treating science, applied mathematics, and computer science together, the book reveals how this knowledge base can be applied to a wider range of real-world problems than computational physics texts normally address. Designed for a one- or two-semester course, A Survey of Computational Physics will also interest anyone who wants a reference on or practical experience in the basics of computational physics. Accessible to advanced undergraduates Real-world problem-solving approach Java codes and applets integrated with text Companion Web site includes videos of lectures
"This book is an introductory course in molecular biology for mathematicians, physicists, and engineers. It covers the basic features of DNA, proteins, and cells but in the context of recent technological advances, such as next-generation sequencing and high-throughput screens, and their applications. This enables readers to move rapidly from the b
During development cells and tissues undergo changes in pattern and form that employ a wider range of physical mechanisms than at any other time in an organism's life. This book demonstrates how physics can be used to analyze these biological phenomena. Written to be accessible to both biologists and physicists, major stages and components of the biological development process are introduced and then analyzed from the viewpoint of physics. The presentation of physical models requires no mathematics beyond basic calculus.
Physicists, when modelling physical systems with a large number of degrees of freedom, and statisticians, when performing data analysis, have developed their own concepts and methods for making the `best' inference. But are these methods equivalent, or not? What is the state of the art in making inferences? The physicists want answers. More: neural computation demands a clearer understanding of how neural systems make inferences; the theory of chaotic nonlinear systems as applied to time series analysis could profit from the experience already booked by the statisticians; and finally, there is a long-standing conjecture that some of the puzzles of quantum mechanics are due to our incomplete understanding of how we make inferences. Matter enough to stimulate the writing of such a book as the present one. But other considerations also arise, such as the maximum entropy method and Bayesian inference, information theory and the minimum description length. Finally, it is pointed out that an understanding of human inference may require input from psychologists. This lively debate, which is of acute current interest, is well summarized in the present work.
This textbook, pitched at the advanced-undergraduate to beginning-graduate level, focuses on mathematical topics of relevance in contemporary physics that are not usually covered in texts at the same level. Its main purpose is to help students appreciate and take advantage of the modern trend of very productive symbiosis between physics and mathematics. Three major areas are covered: (1) linear operators; (2) group representations and Lie algebra representations; (3) topology and differential geometry.The following are noteworthy features of this book: the style of exposition is a fusion of those common in the standard physics and mathematics literatures; the level of exposition varies from quite elementary to moderately advanced, so that the book is of interest to a wide audience; despite the diversity of the topics covered, there is a strong degree of thematic unity; much care is devoted to detailed cross-referencing so that, from any part of the book, the reader can trace easily where specific concepts or techniques are introduced.
This book represents the state-of-the-art in the field through a unique collection of papers from the world's leading researchers in the area of computational modelling in behavioural neuroscience.
The book requires only rudimentary physics knowledge but ability to program computers creatively and to keep the mind open to simple and not so simple models, based in individuals, for the living world around us.* Interdisciplinary coverage* Research oriented* Contains and explains programs* Based on recent discoveries* Little special knowledge required besides programming* Suitable for undergraduate and graduate research projects
This book keeps an eye in the direction of applications of advanced and high performance scientific computing in describing the behavior of natural and constructed systems, e.g. chaos, bifurcation, fractal, Lyapunov exponent, period doubling, Poincaré map, strange attractor etc. With the aid of powerful computers the modem theory of chaos and its geometry, the fractals, and attractors are developed. The concepts of object oriented computing are introduced early in the text and steadily expanded as one progresses through the chapters. The beginning of each chapter is of an introductory nature, followed by practical applications, the discussion of numerical results, theoretical investigations on nonlinear stability and convergence. This is the first complete introduction to process modelling and computing that fully integrates software tools — enabling professionals and students to master critical techniques hands on through computer simulations based on the popular MATLAB environment. The book offers a simple tool for all those oscillations that are travelling through the world, helping them discover its hidden beauty. Many applications as well as results of computer simulations are presented. The center of concern is set on existing as well as emerging continuous methods of investigations useful for researchers, engineers and practitioners active in many and often interdisciplinary fields, where physics, electrochemistry, biology and medicine play a key role. Coverage includes: • Dynamic behavior of nonlinear systems, • Fundamental descriptions of processes exhibiting nonlinear oscillations, • Mechanism and function of structures of nonlinear oscillations’ patterns, • Analysis of dynamical oscillations in electric circuits and systems, • Artificial intelligence models of natural systems, • Nonlinear oscillations in chemistry, biology and medicine, • Oscillations in mechanics and transport systems, • Oscillations in fractional-order systems, • Energy harvesting systems from the surrounding environment. With an insatiable appetite for exploring the surrounding world and doing research, this book can help readers quickly find ways to use new computers and facilitate the quest for greater knowledge and understanding of reality. The reach of novelty of the book ranges from new mathematical ideas to motivating questions and science issues in many subject areas.
Popular among university applicants and their advisers alike, these guides present a wide range of information on a specific degree discipline, laid out in tabular format enabling at-a-glance course comparison.
