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Texts in Computational Science and Engineering
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Título : Elements of Scientific Computing Tipo de documento: documento electrónico Autores: Tveito, Aslak ; SpringerLink (Online service) ; Langtangen, Hans Petter ; Nielsen, Bjørn Frederik ; Cai, Xing Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2010 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 7 Número de páginas: XII, 468 p. 86 illus Il.: online resource ISBN/ISSN/DL: 978-3-642-11299-7 Idioma : Inglés (eng) Palabras clave: Mathematics Bioinformatics Computational biology Computer mathematics Physics intelligence and Numerical Analysis Science Engineering Intelligence Appl. in Life Sciences Clasificación: 51 Matemáticas Resumen: Science used to be experiments and theory, now it is experiments, theory and computations. The computational approach to understanding nature and technology is currently flowering in many fields such as physics, geophysics, astrophysics, chemistry, biology, and most engineering disciplines. This book is a gentle introduction to such computational methods where the techniques are explained through examples. It is our goal to teach principles and ideas that carry over from field to field. You will learn basic methods and how to implement them. In order to gain the most from this text, you will need prior knowledge of calculus, basic linear algebra and elementary programming Nota de contenido: Computing Integrals.- Differential Equations: The First Steps -- Systems of Ordinary Differential Equations -- Nonlinear Algebraic Equations.- The Method of Least Squares.- About Scientific Software -- The Diffusion Equation -- Analysis of the Diffusion Equation -- Parameter Estimation and Inverse Problems. - A Glimpse of Parallel Computing -- Index En línea: http://dx.doi.org/10.1007/978-3-642-11299-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33741 Elements of Scientific Computing [documento electrónico] / Tveito, Aslak ; SpringerLink (Online service) ; Langtangen, Hans Petter ; Nielsen, Bjørn Frederik ; Cai, Xing . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2010 . - XII, 468 p. 86 illus : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 7) .
ISBN : 978-3-642-11299-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Bioinformatics Computational biology Computer mathematics Physics intelligence and Numerical Analysis Science Engineering Intelligence Appl. in Life Sciences Clasificación: 51 Matemáticas Resumen: Science used to be experiments and theory, now it is experiments, theory and computations. The computational approach to understanding nature and technology is currently flowering in many fields such as physics, geophysics, astrophysics, chemistry, biology, and most engineering disciplines. This book is a gentle introduction to such computational methods where the techniques are explained through examples. It is our goal to teach principles and ideas that carry over from field to field. You will learn basic methods and how to implement them. In order to gain the most from this text, you will need prior knowledge of calculus, basic linear algebra and elementary programming Nota de contenido: Computing Integrals.- Differential Equations: The First Steps -- Systems of Ordinary Differential Equations -- Nonlinear Algebraic Equations.- The Method of Least Squares.- About Scientific Software -- The Diffusion Equation -- Analysis of the Diffusion Equation -- Parameter Estimation and Inverse Problems. - A Glimpse of Parallel Computing -- Index En línea: http://dx.doi.org/10.1007/978-3-642-11299-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33741 Ejemplares
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Título : Fundamentals of Scientific Computing Tipo de documento: documento electrónico Autores: Gustafsson, Bertil ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2011 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 8 Número de páginas: XIV, 326 p Il.: online resource ISBN/ISSN/DL: 978-3-642-19495-5 Idioma : Inglés (eng) Palabras clave: Mathematics Computer simulation Bioinformatics Computational biology mathematics Physics Applied Engineering and Numerical Analysis Science Appl. in Life Sciences Appl.Mathematics/Computational Methods of Simulation Modeling Clasificación: 51 Matemáticas Resumen: The book of nature is written in the language of mathematics -- Galileo Galilei How is it possible to predict weather patterns for tomorrow, with access solely to today’s weather data? And how is it possible to predict the aerodynamic behavior of an aircraft that has yet to be built? The answer is computer simulations based on mathematical models – sets of equations – that describe the underlying physical properties. However, these equations are usually much too complicated to solve, either by the smartest mathematician or the largest supercomputer. This problem is overcome by constructing an approximation: a numerical model with a simpler structure can be translated into a program that tells the computer how to carry out the simulation. This book conveys the fundamentals of mathematical models, numerical methods and algorithms. Opening with a tutorial on mathematical models and analysis, it proceeds to introduce the most important classes of numerical methods, with finite element, finite difference and spectral methods as central tools. The concluding section describes applications in physics and engineering, including wave propagation, heat conduction and fluid dynamics. Also covered are the principles of computers and programming, including MATLAB® Nota de contenido: Part I Models and elementary mathematics -- Part II Fundamentals in numerical analysis -- Part III Numerical methods for differential equations -- Part IV Numerical methods for algebraic equations -- Part V Applications -- References -- Index En línea: http://dx.doi.org/10.1007/978-3-642-19495-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33415 Fundamentals of Scientific Computing [documento electrónico] / Gustafsson, Bertil ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2011 . - XIV, 326 p : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 8) .
ISBN : 978-3-642-19495-5
Idioma : Inglés (eng)
Palabras clave: Mathematics Computer simulation Bioinformatics Computational biology mathematics Physics Applied Engineering and Numerical Analysis Science Appl. in Life Sciences Appl.Mathematics/Computational Methods of Simulation Modeling Clasificación: 51 Matemáticas Resumen: The book of nature is written in the language of mathematics -- Galileo Galilei How is it possible to predict weather patterns for tomorrow, with access solely to today’s weather data? And how is it possible to predict the aerodynamic behavior of an aircraft that has yet to be built? The answer is computer simulations based on mathematical models – sets of equations – that describe the underlying physical properties. However, these equations are usually much too complicated to solve, either by the smartest mathematician or the largest supercomputer. This problem is overcome by constructing an approximation: a numerical model with a simpler structure can be translated into a program that tells the computer how to carry out the simulation. This book conveys the fundamentals of mathematical models, numerical methods and algorithms. Opening with a tutorial on mathematical models and analysis, it proceeds to introduce the most important classes of numerical methods, with finite element, finite difference and spectral methods as central tools. The concluding section describes applications in physics and engineering, including wave propagation, heat conduction and fluid dynamics. Also covered are the principles of computers and programming, including MATLAB® Nota de contenido: Part I Models and elementary mathematics -- Part II Fundamentals in numerical analysis -- Part III Numerical methods for differential equations -- Part IV Numerical methods for algebraic equations -- Part V Applications -- References -- Index En línea: http://dx.doi.org/10.1007/978-3-642-19495-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33415 Ejemplares
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Título : Numerical Simulation in Molecular Dynamics : Numerics, Algorithms, Parallelization, Applications Tipo de documento: documento electrónico Autores: Griebel, Michael ; SpringerLink (Online service) ; Zumbusch, Gerhard ; Knapek, Stephan Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2007 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 5 Número de páginas: XII, 476 p. 180 illus., 43 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-540-68095-6 Idioma : Inglés (eng) Palabras clave: Chemistry Chemometrics Physical chemistry Computer simulation mathematics Numerical analysis Physics Simulation and Modeling Computational Science Engineering Analysis Math. Applications in Theoretical, Mathematical Clasificación: 51 Matemáticas Resumen: Particle models play an important role in many applications in physics, chemistry and biology. They can be studied on the computer with the help of molecular dynamics simulations. This book presents in detail both the necessary numerical methods and techniques (linked-cell method, SPME-method, tree codes, multipole technique) and the theoretical background and foundations. It illustrates the aspects modelling, discretization, algorithms and their parallel implementation with MPI on computer systems with distributed memory. Furthermore, detailed explanations are given to the different steps of numerical simulation, and code examples are provided. With the description of the algorithms and the presentation of the results of various simulations from the areas material science, nanotechnology, biochemistry and astrophysics, the reader of this book will be able to write his own programs for molecular dynamics step by step and to run successful experiments Nota de contenido: Computer Simulation — a Key Technology -- From the Schrödinger Equation to Molecular Dynamics -- The Linked Cell Method for Short-Range Potentials -- Parallelization -- Extensions to More Complex Potentials and Molecules -- Time Integration Methods -- Mesh-Based Methods for Long-Range Potentials -- Tree Algorithms for Long-Range Potentials -- Applications from Biochemistry and Biophysics -- Prospects En línea: http://dx.doi.org/10.1007/978-3-540-68095-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34649 Numerical Simulation in Molecular Dynamics : Numerics, Algorithms, Parallelization, Applications [documento electrónico] / Griebel, Michael ; SpringerLink (Online service) ; Zumbusch, Gerhard ; Knapek, Stephan . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2007 . - XII, 476 p. 180 illus., 43 illus. in color : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 5) .
ISBN : 978-3-540-68095-6
Idioma : Inglés (eng)
Palabras clave: Chemistry Chemometrics Physical chemistry Computer simulation mathematics Numerical analysis Physics Simulation and Modeling Computational Science Engineering Analysis Math. Applications in Theoretical, Mathematical Clasificación: 51 Matemáticas Resumen: Particle models play an important role in many applications in physics, chemistry and biology. They can be studied on the computer with the help of molecular dynamics simulations. This book presents in detail both the necessary numerical methods and techniques (linked-cell method, SPME-method, tree codes, multipole technique) and the theoretical background and foundations. It illustrates the aspects modelling, discretization, algorithms and their parallel implementation with MPI on computer systems with distributed memory. Furthermore, detailed explanations are given to the different steps of numerical simulation, and code examples are provided. With the description of the algorithms and the presentation of the results of various simulations from the areas material science, nanotechnology, biochemistry and astrophysics, the reader of this book will be able to write his own programs for molecular dynamics step by step and to run successful experiments Nota de contenido: Computer Simulation — a Key Technology -- From the Schrödinger Equation to Molecular Dynamics -- The Linked Cell Method for Short-Range Potentials -- Parallelization -- Extensions to More Complex Potentials and Molecules -- Time Integration Methods -- Mesh-Based Methods for Long-Range Potentials -- Tree Algorithms for Long-Range Potentials -- Applications from Biochemistry and Biophysics -- Prospects En línea: http://dx.doi.org/10.1007/978-3-540-68095-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34649 Ejemplares
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Título : A Primer on Scientific Programming with Python Tipo de documento: documento electrónico Autores: Langtangen, Hans Petter ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2009 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 6 Número de páginas: XXVIII, 694 p Il.: online resource ISBN/ISSN/DL: 978-3-642-02475-7 Idioma : Inglés (eng) Palabras clave: Computer science Software engineering programming Mathematics mathematics Physics Science of Computing Computational and Engineering Programming Techniques Engineering/Programming Operating Systems Numerical Clasificación: 51 Matemáticas Resumen: Theaimofthisbookistoteachcomputerprogrammingusingexamples from mathematics and the natural sciences. We have chosen to use the Python programming language because it combines remarkable power with very clean, simple, and compact syntax. Python is easy to learn and very well suited for an introduction to computer programming. Python is also quite similar to Matlab and a good language for doing mathematical computing. It is easy to combine Python with compiled languages, like Fortran, C, and C++, which are widely used languages forscienti?ccomputations.AseamlessintegrationofPythonwithJava is o?ered by a special version of Python called Jython. The examples in this book integrate programming with appli- tions to mathematics, physics, biology, and ?nance. The reader is - pected to have knowledge of basic one-variable calculus as taught in mathematics-intensive programs in high schools. It is certainly an - vantage to take a university calculus course in parallel, preferably c- taining both classical and numerical aspects of calculus. Although not strictly required, a background in high school physics makes many of the examples more meaningful Nota de contenido: Computing with Formulas -- Basic Constructions -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Sequences and Difference Equations -- Files, Strings, and Dictionaries -- to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming En línea: http://dx.doi.org/10.1007/978-3-642-02475-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34071 A Primer on Scientific Programming with Python [documento electrónico] / Langtangen, Hans Petter ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2009 . - XXVIII, 694 p : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 6) .
ISBN : 978-3-642-02475-7
Idioma : Inglés (eng)
Palabras clave: Computer science Software engineering programming Mathematics mathematics Physics Science of Computing Computational and Engineering Programming Techniques Engineering/Programming Operating Systems Numerical Clasificación: 51 Matemáticas Resumen: Theaimofthisbookistoteachcomputerprogrammingusingexamples from mathematics and the natural sciences. We have chosen to use the Python programming language because it combines remarkable power with very clean, simple, and compact syntax. Python is easy to learn and very well suited for an introduction to computer programming. Python is also quite similar to Matlab and a good language for doing mathematical computing. It is easy to combine Python with compiled languages, like Fortran, C, and C++, which are widely used languages forscienti?ccomputations.AseamlessintegrationofPythonwithJava is o?ered by a special version of Python called Jython. The examples in this book integrate programming with appli- tions to mathematics, physics, biology, and ?nance. The reader is - pected to have knowledge of basic one-variable calculus as taught in mathematics-intensive programs in high schools. It is certainly an - vantage to take a university calculus course in parallel, preferably c- taining both classical and numerical aspects of calculus. Although not strictly required, a background in high school physics makes many of the examples more meaningful Nota de contenido: Computing with Formulas -- Basic Constructions -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Sequences and Difference Equations -- Files, Strings, and Dictionaries -- to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming En línea: http://dx.doi.org/10.1007/978-3-642-02475-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34071 Ejemplares
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Título : A Primer on Scientific Programming with Python Tipo de documento: documento electrónico Autores: Langtangen, Hans Petter ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2011 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 6 Número de páginas: XXX, 706 p. 72 illus., 28 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-642-18366-9 Idioma : Inglés (eng) Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science Nota de contenido: Computing with Formulas -- Loops and Lists -- Functions and Branching -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Files, Strings and Dictionaries -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus.- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-18366-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33411 A Primer on Scientific Programming with Python [documento electrónico] / Langtangen, Hans Petter ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2011 . - XXX, 706 p. 72 illus., 28 illus. in color : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 6) .
ISBN : 978-3-642-18366-9
Idioma : Inglés (eng)
Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science Nota de contenido: Computing with Formulas -- Loops and Lists -- Functions and Branching -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Files, Strings and Dictionaries -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus.- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-18366-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33411 Ejemplares
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