Showing posts with label Methods. Show all posts
Showing posts with label Methods. Show all posts

Mathematical Methods in Engineering

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Mathematical Methods in Engineering Overview


This book contains some of the contributions that have been carefully selected and peer-reviewed, which were presented at the International Symposium MME06 Mathematical Methods in Engineering, held in Cankaya University, Ankara, April 2006. The Symposium provided a setting for discussing recent developments in Fractional Mathematics, Neutrices and Generalized Functions, Boundary Value Problems, Applications of Wavelets, Dynamical Systems and Control Theory.




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Circuit Simulation Methods and Algorithms (Electronic Engineering Systems)

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Circuit Simulation Methods and Algorithms (Electronic Engineering Systems) Overview


Circuit Simulation Methods and Algorithms provides a step-by-step theoretical consideration of methods, techniques, and algorithms in an easy-to-understand format. Many illustrations explain more difficult problems and present instructive circuits.
The book works on three levels:
  • The simulator-user level for practitioners and students who want to better understand circuit simulators.
  • The basic theoretical level, with examples, dedicated to students and beginning researchers.
  • The thorough level for deep insight into circuit simulation based on computer experiments using PSPICE and OPTIMA.
    Only basic mathematical knowledge, such as matrix algebra, derivatives, and integrals, is presumed.



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    Modeling of Metal Forming and Machining Processes: by Finite Element and Soft Computing Methods (Engineering Materials and Processes)

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    Modeling of Metal Forming and Machining Processes: by Finite Element and Soft Computing Methods (Engineering Materials and Processes) Overview


    The physics of metal forming and metal removing is normally expressed using non-linear partial differential equations which can be solved using the finite element method (FEM). However, when the process parameters are uncertain and/or the physics of the process is not well understood, soft computing techniques can be used with FEM or alone to model the process.

    Using FEM, fuzzy set theory and neural networks as modeling tools; Modeling of Metal Forming and Machining Processes provides a complete treatment of metal forming and machining, and includes:

    an explanation of FEM and its application to the modeling of manufacturing processes;

    a discussion of the numerical difficulties of FEM;

    chapters on the application of soft computing techniques in this modeling process.

    The algorithms and solved examples included make Modeling of Metal Forming and Machining Processes of value to postgraduates, senior undergraduates, lecturers and researchers in these fields. R&D engineers and consultants for the manufacturing industry will also find it of use.




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    Reliable Methods for Computer Simulation, Volume 33: Error Control and Posteriori Estimates (Studies in Mathematics and its Applications)

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    Reliable Methods for Computer Simulation, Volume 33: Error Control and Posteriori Estimates (Studies in Mathematics and its Applications) Overview


    Recent decades have seen a very rapid success in developing numerical methods based on explicit control over approximation errors. It may be said that nowadays a new direction is forming in numerical analysis, the main goal of which is to develop methods ofreliable computations. In general, a reliable numerical method must solve two basic problems: (a) generate a sequence of approximations that converges to a solution and (b) verify the accuracy of these approximations. A computer code for such a method must consist of two respective blocks: solver and checker.

    In this book, we are chiefly concerned with the problem (b) and try to present the main approaches developed for a posteriori error estimation in various problems.

    The authors try to retain a rigorous mathematical style, however, proofs are constructive whenever possible and additional mathematical knowledge is presented when necessary. The book contains a number of new mathematical results and lists a posteriori error estimation methods that have been developed in the very recent time.

    · computable bounds of approximation errors
    · checking algorithms
    · iteration processes
    · finite element methods
    · elliptic type problems
    · nonlinear variational problems
    · variational inequalities


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    Domain Decomposition: Parallel Multilevel Methods for Elliptic Partial Differential Equations

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    Domain Decomposition: Parallel Multilevel Methods for Elliptic Partial Differential Equations Overview


    This book presents an easy-to-read discussion of domain decomposition algorithms, their implementation and analysis. The authors carefully explain the relationship between domain decomposition and multigrid methods at an elementary level, and they discuss the implementation of domain decomposition methods on massively parallel supercomputers. They fully describe and explain all algorithms and carefully develop a mathematical framework for the analysis and complete understanding of the methods. In addition, they include numerous numerical examples to demonstrate the behavior of this important class of numerical methods.


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    Fundamental Numerical Methods for Electrical Engineering (Lecture Notes in Electrical Engineering)

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    Fundamental Numerical Methods for Electrical Engineering (Lecture Notes in Electrical Engineering) Overview


    The book presents fundamental numerical methods which are most frequently applied in the electrical (electronic) engineering. Mathematical problems are solved step by step, and all methods discussed are illustrated with real-world examples of applications.




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    Methods in Neuronal Modeling - 2nd Edition: From Ions to Networks (Computational Neuroscience)

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    Methods in Neuronal Modeling - 2nd Edition: From Ions to Networks (Computational Neuroscience) Overview


    State-of-the-art neuronal modeling techniques. For computational neuroscientists and theoretical neurobiologists.


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    Simulation Modeling Methods: To Reduce Risks and Increase Performance (CD-ROM included)

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    Simulation Modeling Methods: To Reduce Risks and Increase Performance (CD-ROM included) Overview


    Computer simulation modeling, the new force in business, allows managers to see the results of a process change before committing time and resources to it. The Simulation Modeling Toolkit is vital to understanding numerous applications of this important process. Its methods and techniques will help any reader reduce time and risk in developing new products and serving customers, and the CD-ROM insert enables the user to create and run simulations from start to finish.


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    Computational Systems Bioinformatics -- Methods And Biomedical Applications

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    Computational Systems Bioinformatics -- Methods And Biomedical Applications Overview


    Computational systems biology is a new and rapidly developing field of research, concerned with understanding the structure and processes of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data and image analysis methods. By focusing on either information processing of biological data or on modeling physical and chemical processes of biosystems, and in combination with the recent breakthrough in deciphering the human genome, computational systems biology is guaranteed to play a central role in disease prediction and preventive medicine, gene technology and pharmaceuticals, and other biotechnology fields.

    This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach in computational biology, it focuses on recurrent themes in bioinformatics, biomedical applications, and future directions for research.

    Contents: Introduction; Mathematical, Statistical, and Data Mining Principles; Missing Value Estimation Using KNN and Bayesian Methods; Normalization, Scaling, and Discretization; Cross-Platform Comparison; Discovering Differential Biomarkers; Gene Selection and Classification; Gene Clustering; Gene Prediction; Reverse Engineering: Gene Regulatory Network Construction and Its Behavior; Motif Detection and Transcription Factor Binding Site (TFBS) Identification; Integrated Microarray and Gene Sequence Analysis; Protein Structure Informatics; Biomarker Discovery from Proteomics; Bioimaging Informatics; Conclusions.


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    Introducing Multilevel Modeling (Introducing Statistical Methods series)

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    Kreft and DeLeeuw's Introducing Multilevel Modeling was written to mercifully place only limited mathematical demands on readers. It includes an interesting and readable account of intercepts and slopes as outcomes. However, in common with most other texts, it fails to accessibly develop parallels between multilevel modeling and more widely understood procedures. Instead, the authors' intent seems to be to highlight differences, perhaps to make the distinctiveness, virtues, and limitations of multilevel modeling clear to the reader. Whatever the value of their approach, I find it much easier to understand multilevel analysis as an extension of multiple regression, a connection which Kreft and DeLeeuw do not develop.

    Simple examples are presented throughout the book using MLn software. Models with more than two levels are not discussed. Growth models are mentioned in passing. The authors emphasize that the constraints imposed by multilevel analysis make it best suited to relatively simple models, but I think they over-emphasize this judgment. Models much more complex than those used in this text are usefully employed and widely reported in a variety of books and journal articles.

    The authors also treat close calls with regard to statistical significance as of dubious value. The reason for this is not given, and I much prefer setting an alpha level and then sticking with it, rather than second-guessing results.

    This is a brief text that addresses some issues of importance in the Frequently Asked Questions section at the end of the book. It is not a comprehensive reference, but that was not its intended purpose. It reads especially well the second time through, and gives a good deal of needed attention to centering, an important topic that is glossed over in most other multilevel texts.




    Introducing Multilevel Modeling (Introducing Statistical Methods series) Overview


    This is the first accessible and practical guide to using multilevel models in social research.

    Multilevel approaches are becoming increasingly important in social, behavioural, and educational research and it is clear from recent developments that such models are seen as being more realistic, and potentially more revealing, than ordinary regression models.

    While other books describe these multilevel models in considerable detail none focuses on the practical issues and potential problems of doing multilevel analyses that are covered in Introducing Multilevel Modeling.

    The authors' approach is user-oriented and the formal mathematics and statistics are kept to a minimum. Other key fe


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    Multivariate Nonparametric Methods with R: An approach based on spatial signs and ranks (Lecture Notes in Statistics)

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    Multivariate Nonparametric Methods with R: An approach based on spatial signs and ranks (Lecture Notes in Statistics) Overview


    This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 norm is just replaced by different L1 norms, observation vectors are replaced by spatial signs and ranks, and so on. A unified methodology starting with the simple one-sample multivariate location problem and proceeding to the general multivariate multiple linear regression case is presented. Companion estimates and tests for scatter matrices are considered as well. The R package MNM is available for computation of the procedures. This monograph provides an up-to-date overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. The classical book by Puri and Sen (1971) uses marginal signs and ranks and different type of L1 norm. The book may serve as a textbook and a general reference for the latest developments in the area. Readers are assumed to have a good knowledge of basic statistical theory as well as matrix theory.


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    Progress in Computational Physics of Matter: Methods, Software and Applications

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    Progress in Computational Physics of Matter: Methods, Software and Applications Overview


    The aim of this text is to describe some of the recent advances, through computer simulation in a broad sense, in the understanding of the complex processes occurring in solid and liquids. The rapid growth of computer power, including the new parallel processors, has stimulated a ferment of new theoretical and computational ideas, which have been developed in particular by the authors in a pluriennal research project supported by Consiglio Nazionale delle Ricerche (CNR) for the development of novel software for large scale computations. The book covers advances in "ab initio" (Car-Parrinello) molecular dynamics, quantum Monte Carlo simulations, self-consistent density functional computation of electronic states, classical molecular dynamics simulation of thermodynamic processes, chemical reactions and transport properties. Besides the description of the results of these techniques in leading edge applications, the book addresses specific aspects of the algorithms and software which have been developed by the authors in order to implement in an efficient way the new theoretical advances in these computationally intensive problems. These aspects which are generally not discussed in any detail in the literature, can be of great help for newcomers in the field.


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