Mathematical Models Of The Cell And Cell Associated Objects
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Mathematical Models Of The Cell And Cell Associated Objects
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Author : Viktor V. Ivanov
language : en
Publisher: Elsevier
Release Date : 2006-05-10
Mathematical Models Of The Cell And Cell Associated Objects written by Viktor V. Ivanov and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-10 with Computers categories.
This book gives the reader a survey of hundreds results in the field of the cell and cell associated objects modeling. Applications to modeling in the areas of AIDS, cancers and life longevity are investigated in this book. - Introduces and proves fundamental properties of evolutionary systems on optimal distribution of their various resources on their internal and external functions - Gives detailed analysis of applications to modeling AIDS, cancers, and life longevity - Introducing and grounding the respective numerical algorithms and software - Detailed analysis of hundreds of scientific works in the field of mathematical modeling of the cell and cell associated objects
Mathematical Models In Biology
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Author : Leah Edelstein-Keshet
language : en
Publisher: SIAM
Release Date : 1988-01-01
Mathematical Models In Biology written by Leah Edelstein-Keshet and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-01-01 with Mathematics categories.
Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. A favorite in the mathematical biology community, it shows how relatively simple mathematics can be applied to a variety of models to draw interesting conclusions. Connections are made between diverse biological examples linked by common mathematical themes. A variety of discrete and continuous ordinary and partial differential equation models are explored. Although great advances have taken place in many of the topics covered, the simple lessons contained in this book are still important and informative. Audience: the book does not assume too much background knowledge--essentially some calculus and high-school algebra. It was originally written with third- and fourth-year undergraduate mathematical-biology majors in mind; however, it was picked up by beginning graduate students as well as researchers in math (and some in biology) who wanted to learn about this field.
Computational Methods For Modeling Of Nonlinear Systems By Anatoli Torokhti And Phil Howlett
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Author : Anatoli Torokhti
language : en
Publisher: Elsevier
Release Date : 2007-04-11
Computational Methods For Modeling Of Nonlinear Systems By Anatoli Torokhti And Phil Howlett written by Anatoli Torokhti and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-11 with Mathematics categories.
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation - Non-Lagrange interpolation - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering
Information Theoretic Methods For Estimating Of Complicated Probability Distributions
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Author : Zhi Zong
language : en
Publisher: Elsevier
Release Date : 2006-08-15
Information Theoretic Methods For Estimating Of Complicated Probability Distributions written by Zhi Zong and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-15 with Mathematics categories.
Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions. Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neural networks and quality control. Simple distribution forms such as Gaussian, exponential or Weibull distributions are often employed to represent the distributions of the random variables under consideration, as we are taught in universities. In engineering, physical and social science applications, however, the distributions of many random variables or random vectors are so complicated that they do not fit the simple distribution forms at al. Exact estimation of the probability distribution of a random variable is very important. Take stock market prediction for example. Gaussian distribution is often used to model the fluctuations of stock prices. If such fluctuations are not normally distributed, and we use the normal distribution to represent them, how could we expect our prediction of stock market is correct? Another case well exemplifying the necessity of exact estimation of probability distributions is reliability engineering. Failure of exact estimation of the probability distributions under consideration may lead to disastrous designs. There have been constant efforts to find appropriate methods to determine complicated distributions based on random samples, but this topic has never been systematically discussed in detail in a book or monograph. The present book is intended to fill the gap and documents the latest research in this subject. Determining a complicated distribution is not simply a multiple of the workload we use to determine a simple distribution, but it turns out to be a much harder task. Two important mathematical tools, function approximation and information theory, that are beyond traditional mathematical statistics, are often used. Several methods constructed based on the two mathematical tools for distribution estimation are detailed in this book. These methods have been applied by the author for several years to many cases. They are superior in the following senses: (1) No prior information of the distribution form to be determined is necessary. It can be determined automatically from the sample; (2) The sample size may be large or small; (3) They are particularly suitable for computers. It is the rapid development of computing technology that makes it possible for fast estimation of complicated distributions. The methods provided herein well demonstrate the significant cross influences between information theory and statistics, and showcase the fallacies of traditional statistics that, however, can be overcome by information theory. Key Features: - Density functions automatically determined from samples - Free of assuming density forms - Computation-effective methods suitable for PC- density functions automatically determined from samples- Free of assuming density forms- Computation-effective methods suitable for PC
Mathematical Models In Biology
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Author : Elizabeth Spencer Allman
language : en
Publisher: Cambridge University Press
Release Date : 2004
Mathematical Models In Biology written by Elizabeth Spencer Allman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Mathematics categories.
This introductory textbook on mathematical biology focuses on discrete models across a variety of biological subdisciplines. Biological topics treated include linear and non-linear models of populations, Markov models of molecular evolution, phylogenetic tree construction, genetics, and infectious disease models. The coverage of models of molecular evolution and phylogenetic tree construction from DNA sequence data is unique among books at this level. Computer investigations with MATLAB are incorporated throughout, in both exercises and more extensive projects, to give readers hands-on experience with the mathematical models developed. MATLAB programs accompany the text. Mathematical tools, such as matrix algebra, eigenvector analysis, and basic probability, are motivated by biological models and given self-contained developments, so that mathematical prerequisites are minimal.
L System Fractals
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Author : Jibitesh Mishra
language : en
Publisher: Elsevier
Release Date : 2007-01-08
L System Fractals written by Jibitesh Mishra and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-08 with Computers categories.
L-System Fractals covers all the fundamental aspects of generating fractals through L-system. Also it provides insight to various researches in this area for generating fractals through L-system approach & estimating dimensions. Also it discusses various applications of L-system fractals. - Fractals generated from L-System including hybrid fractals - Dimension calculation for L-system fractals - Images and codes for L-system fractals - Research directions in the area of L-system fractals - Usage of various freely downloadable tools in this area
Stochastic Modelling In Process Technology
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Author : Herold G. Dehling
language : en
Publisher: Elsevier
Release Date : 2007-07-03
Stochastic Modelling In Process Technology written by Herold G. Dehling and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-03 with Mathematics categories.
There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computing the probability distribution for a single particle's position in the process vessel, and/or the particle's properties, as a function of time, rather than - as is traditionally done - basing the model on the formulation and solution of differential conservation equations. Using this technique can greatly simplify the formulation of a model, and even make modelling possible for processes so complex that the traditional method is impracticable. Stochastic modelling has sporadically been used in various branches of process technology under various names and guises. This book gives, as the first, an overview of this work, and shows how these techniques are similar in nature, and make use of the same basic mathematical tools and techniques. The book also demonstrates how stochastic modelling may be implemented by describing example cases, and shows how a stochastic model may be formulated for a case, which cannot be described by formulating and solving differential balance equations. - Introduction to stochastic process modelling as an alternative modelling technique - Shows how stochastic modelling may be succesful where the traditional technique fails - Overview of stochastic modelling in process technology in the research literature - Illustration of the principle by a wide range of practical examples - In-depth and self-contained discussions - Points the way to both mathematical and technological research in a new, rewarding field
Dynamical Systems Method For Solving Nonlinear Operator Equations
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Author : Alexander G. Ramm
language : en
Publisher: Elsevier
Release Date : 2006-09-25
Dynamical Systems Method For Solving Nonlinear Operator Equations written by Alexander G. Ramm and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-25 with Mathematics categories.
Dynamical Systems Method for Solving Nonlinear Operator Equations is of interest to graduate students in functional analysis, numerical analysis, and ill-posed and inverse problems especially. The book presents a general method for solving operator equations, especially nonlinear and ill-posed. It requires a fairly modest background and is essentially self-contained. All the results are proved in the book, and some of the background material is also included. The results presented are mostly obtained by the author. - Contains a systematic development of a novel general method, the dynamical systems method, DSM for solving operator equations, especially nonlinear and ill-posed - Self-contained, suitable for wide audience - Can be used for various courses for graduate students and partly for undergraduates (especially for RUE classes)
Numerical Time Dependent Partial Differential Equations For Scientists And Engineers
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Author : Moysey Brio
language : en
Publisher: Academic Press
Release Date : 2010-09-21
Numerical Time Dependent Partial Differential Equations For Scientists And Engineers written by Moysey Brio and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-21 with Mathematics categories.
It is the first text that in addition to standard convergence theory treats other necessary ingredients for successful numerical simulations of physical systems encountered by every practitioner. The book is aimed at users with interests ranging from application modeling to numerical analysis and scientific software development. It is strongly influenced by the authors research in in space physics, electrical and optical engineering, applied mathematics, numerical analysis and professional software development. The material is based on a year-long graduate course taught at the University of Arizona since 1989. The book covers the first two-semesters of a three semester series. The second semester is based on a semester-long project, while the third semester requirement consists of a particular methods course in specific disciplines like computational fluid dynamics, finite element method in mechanical engineering, computational physics, biology, chemistry, photonics, etc.The first three chapters focus on basic properties of partial differential equations, including analysis of the dispersion relation, symmetries, particular solutions and instabilities of the PDEs; methods of discretization and convergence theory for initial value problems. The goal is to progress from observations of simple numerical artifacts like diffusion, damping, dispersion, and anisotropies to their analysis and management technique, as it is not always possible to completely eliminate them.In the second part of the book we cover topics for which there are only sporadic theoretical results, while they are an integral part and often the most important part for successful numerical simulation. We adopt a more heuristic and practical approach using numerical methods of investigation and validation. The aim is teach students subtle key issues in order to separate physics from numerics. The following topics are addressed: Implementation of transparent and absorbing boundary conditions; Practical stability analysis in the presence of the boundaries and interfaces; Treatment of problems with different temporal/spatial scales either explicit or implicit; preservation of symmetries and additional constraints; physical regularization of singularities; resolution enhancement using adaptive mesh refinement and moving meshes. - Self contained presentation of key issues in successful numerical simulation - Accessible to scientists and engineers with diverse background - Provides analysis of the dispersion relation, symmetries, particular solutions and instabilities of the partial differential equations
Mathematical Models In Molecular Cellular Biology
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Author : Lee A. Segel
language : en
Publisher: CUP Archive
Release Date : 1980
Mathematical Models In Molecular Cellular Biology written by Lee A. Segel and has been published by CUP Archive this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with Mathematics categories.
Interest in theoretical biology is rapidly growing and this 1981 book attempts to make the theory more accessible to experimentalists. Its primary purpose is to demonstrate to experimental molecular and cellular biologists the possible usefulness of mathematical models. Biologists with a basic command of calculus should be able to learn from the book what assumptions are implied by various types of equations, to understand in broad outline a number of major theoretical concepts, and to be aware of some of the difficulties connected with analytical and numerical solutions of mathematical problems. Thus they should be able to appreciate the significance of theoretical papers in their fields and to communicate usefully with theoreticians in the course of their work.