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There is no branch of mathematics, however abstract, which may not some day be applied to phenomena of the real world.
Nikolai Ivanovich Lobachevsky (December 1, 1792–February 24, 1856) His work is mainly on hyperbolic geometry, also known as Lobachevskian geometry.
The rapid growth of science and technology during the last few decades has made a tremendous change to the nature of various mathematical problems. It is not easy to solve these new problems for analytical solutions by conventional methods. In fact, the study of these mathematical problems for analytical solutions is not only regarded as a difficult endeavor, rather it is almost impossible to get analytical solutions in many cases. The tools for analysis and for obtaining the analytical solutions of complex and nonlinear mathematical systems are limited to very few special categories. Due to this reason, when confronted with such complex problems we usually simplify them by invoking certain restrictions on the problem and then solve it. But these solutions, however, fail to render much needed information about the system. These shortcomings of analytical solutions lead us to seek alternates, and various numerical techniques developed for different types of mathematical problems seem to be excellent options. During the last century, the numerical techniques have witnessed a veritable explosion in research, both in their application to complex mathematical systems and in the very development of these techniques. At many places in this book, we will compare numerical techniques with analytical techniques, and point out various problems which can not be solved through analytical techniques, and to which numerical techniques provide quite good approximate solutions.
Many researchers are using numerical techniques to investigate research problems. Numerical techniques are now widely used in a lot of engineering and science fields. Almost all universities now offer courses on introductory and advanced computer-oriented numerical methods to their engineering and science students, keeping in mind the utilization merits of these techniques. In addition, computer-oriented problems are part of various other courses of engineering/technology.
It gives me immense pleasure in presenting the book to our esteemed readers. This book is written keeping several goals in mind. It provides essential information on various numerical techniques to the students from various engineering and science streams.
There's no sense in being precise when you don't even know what you're talking about.
John von Neumann (December 28, 1903–February 8, 1957) He was a great mathematician, physicist and computer scientist who had many research investigations to his credit.
Mathematics is the science which draws necessary conclusions.
Benjamin Peirce (April 4, 1809–October 6, 1880) He was a mathematician who had contributed to algebra, number theory, statistics and mechanics.
Parabolic Equation (Heat Conduction or Diffusion Equation)Elliptic Equation (Laplace and Poisson Equations)Hyperbolic Equation (Wave Equation)
Most of the problems posed by nature, and which are of interest to physicists and mathematicians are usually governed by a single or a system of differential equations. In general, a physical system involves more than one independent variable; in that case, our mathematical model contains partial differential equations (PDEs). PDEs play a vital role in the study of many branches of applied sciences and engineering; for example, fluid dynamics, heat transfer, elasticity, electromagnetic theory, optics, plasma physics, quantum mechanics, etc. In fact, the theories of modern physics, generally involve a mathematical model, as far as possible it is a set of PDEs. We first solve the mathematical model for solutions and then come to mathematical and physical interpretations of these solutions. So it is necessary to solve the mathematical model to study the physical system. Often, it is very difficult to solve these sets of PDEs explicitly for exact solutions. Consequently, numerical methods are applied to obtain approximate solutions of these equations. In fact, there is much current interest in obtaining numerical solutions of the PDEs.
The finite difference method is a simple and most commonly used method to solve PDEs. In this method, various derivatives in the partial differential equation are replaced by their finite difference approximations, and the PDE is converted to a set of linear algebraic equations. This system of linear equations can be solved by any iterative procedure discussed in Chapter 5. Then, the solution of PDE is the solution of this system of linear equations. An important advantage of this method is that the most of the calculations can be carried out on the computer, and hence the solution is easy to obtain.
Gain a detailed understanding of the fundamental concepts of chemistry and their engineering applications with this fully revised second edition. Catering to the needs of first and second semester undergraduate students from all branches of engineering taking courses on engineering chemistry, it offers new material on topics such as periodic properties, structure and bonding, gaseous states, ionic equilibrium, oxidation and reduction, Werner's coordination theory, Sidgwick coordination theory, valence bond theory, crystal field theory, bonding in coordination compounds, and isomerism in coordination compounds. Lucid language and an easy-to-learn approach help students to understand the basic concepts, use them to construct engineering materials, and solve problems associated with them. Each chapter is further strengthened by numerous examples and review questions.
Developed specifically for students in the behavioral and brain sciences, this is the only textbook that provides an accessible and practical overview of the range of human neuroimaging techniques. Methods covered include functional and structural magnetic resonance imaging, positron emission tomography, electroencephalography, magnetoencephalography, multimodal imaging, and various brain stimulation methods. Experimental design, image processing, and statistical inference are also addressed, with chapters for both basic and more advanced data analyses. Key concepts are illustrated through research studies on the relationship between brain and behavior, and practice questions are included throughout to test knowledge and aid self-study. Offering just the right amount of detail for understanding how major imaging techniques can be applied to answer neuroscientific questions, and the practical skills needed for future research, this is an essential text for advanced undergraduate and graduate students in psychology, neuroscience, and cognitive science programs taking introductory courses on human neuroimaging.
Philosophy of logic is a fundamental part of philosophical study, and one which is increasingly recognized as being immensely important in relation to many issues in metaphysics, metametaphysics, epistemology, philosophy of mathematics, and philosophy of language. This textbook provides a comprehensive and accessible introduction to topics including the objectivity of logical inference rules and its relevance in discussions of epistemological relativism, the revived interest in logical pluralism, the question of logic's metaphysical neutrality, and the demarcation between logic and mathematics. Chapters in the book cover the state of the art in contemporary philosophy of logic, and allow students to understand the philosophical relevance of these debates without having to contend with complex technical arguments. This will be a major new resource for students working on logic, as well as for readers seeking a better understanding of philosophy of logic in its wider context.