الصفحة 9
الصفحة 9
Introductory Statistics with R
R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development. This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. A supplementary R package can be downloaded and contains the data sets.
Introduction to Stochastic Integration
The theory of stochastic integration, also called the Ito calculus, has a large spectrum of applications in virtually every scientific area involving random functions, but it can be a very difficult subject for people without much mathematical background. The Ito calculus was originally motivated by the construction of Markov diffusion processes from infinitesimal generators. Previously, the construction of such processes required several steps, whereas Ito constructed these diffusion processes directly in a single step as the solutions of stochastic integral equations associated with the infinitesimal generators. Moreover, the properties of these diffusion processes can be derived from the stochastic integral equations and the Ito formula. This introductory textbook on stochastic integration provides a concise introduction to the Ito calculus
Introduction to Optics
Since the discovery of the laser in 1960 and optical fibers in 1970, optics has undergone dramatic changes that accentuate its multi-disciplinary character. This text covers essential concepts and reports the key developments and progress in current knowledge in the field. Inspired by the style of Richard Feynman, the method of presentation emphasizes "telling" optics, rather than deducing it from fundamental laws, as well as tactfully using mathematical tools so as not to obscure the physical phenomena of interest. For its excellent teaching approach, the book received the Arnulf-Francon Award of the French Optical Society. The concepts are formulated in a way such that the necessary mathematical tools do not hinder comprehension of the phenomena. Global in vision, the book can also be used as a reference. In addition to the traditional aspects of optics, it includes the tools and methods currently used by researchers and engineers, as well as explanation and implications of the most recent developments.
Introduction to Mathematical Systems Theory : Linear Systems, Identification and Control
This book provides an introduction to the theory of linear systems and control for students in business mathematics, econometrics, computer science, and engineering. The focus is on discrete time systems, which are the most relevant in business applications, as opposed to continuous time systems, requiring less mathematical preliminaries. The subjects treated are among the central topics of deterministic linear system theory: controllability, observability, realization theory, stability and stabilization by feedback, LQ-optimal control theory. Kalman filtering and LQC-control of stochastic systems are also discussed, as are modeling, time series analysis and model specification, along with model validation.
Introduction to Machine Learning with Applications in Information Security
Provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.
Introduction to Lie Algebras
This book provides an elementary introduction to Lie algebras. It starts with basic concepts. A section on low-dimensional Lie algebras provides readers with experience of some useful examples. This is followed by a discussion of solvable Lie algebras and a strategy towards a classification of finite-dimensional complex Lie algebras. The next chapters cover Engel's theorem, Lie's theorem and Cartan's criteria and introduce some representation theory. The root-space decomposition of a semisimple Lie algebra is discussed, and the classical Lie algebras studied in detail. The authors also classify root systems, and give an outline of Serre's construction of complex semisimple Lie algebras. An overview of further directions then concludes the book and shows the high degree to which Lie algebras influence present-day mathematics.The only prerequisite is some linear algebra and an appendix summarizes the main facts that are needed. The treatment is kept as simple as possible with no attempt at full generality.
Introduction to Fuzzy Logic using MATLAB
Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
Introduction to finite element analysis : A textbook for engineering students
Covers the basic concepts and applications of finite element analysis. It is specifically aimed at introducing this advanced topic to undergraduate-level engineering students and practicing engineers in a lucid manner. It also introduces a structural and heat transfer analysis software FEASTSMT which has wide applications in civil, mechanical, nuclear and automobile engineering domains.
Introduction to Engineering Statistics and Six Sigma : Statistical Quality Control and Design of Experiments and Systems
Introduction to Engineering Statistics and Six Sigma contains precise descriptions of all of the many related methods and details case studies showing how they have been applied in engineering and business to achieve millions of dollars of savings. Specifically, the methods introduced include many kinds of design of experiments (DOE) and statistical process control (SPC) charting approaches, failure mode and effects analysis (FMEA), formal optimization, genetic algorithms, gauge reproducibility and repeatability (R&R), linear regression, neural nets, simulation, quality function deployment (QFD) and Taguchi methods. A major goal of the book is to help the reader to determine exactly which methods to apply in which situation and to predict how and when the methods might not be effective.
Introduction to Empirical Processes and Semiparametric Inference
This book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. The targeted audience includes statisticians, biostatisticians, and other researchers with a background in mathematical statistics who have an interest in learning about and doing research in empirical processes and semiparametric inference but who would like to have a friendly and gradual introduction to the area. The book can be used either as a research reference or as a textbook. The level of the book is suitable for a second year graduate course in statistics or biostatistics, provided the students have had a year of graduate level mathematical statistics and a semester of probability.
Introduction to Computational Optimization Models for Production Planning in a Supply Chain
In this book we strive to provide models that capture many of the - tails faced by ?rms operating in a modern supply chain, but we stop short of proposing models for economic analysis of the entire multi-player chain. In other words, we produce models that are useful for planning within a supply chain rather than models for planning the supply chain. The usefulness of the models is enhanced greatly by the fact that they have been implemented - ing computer modeling languages. Implementations are shown in Chapter 7, which allows solutions to be found using a computer.
Introduction to Bayesian Scientific Computing : Ten Lectures on Subjective Computing
Inverse problems are closely related to statistical inference problems, where the observations are used to infer on an underlying probability distribution. This connection between statistical inference and inverse problems is a central topic of the book. Inverse problems are typically ill-posed: small uncertainties in data may propagate in huge uncertainties in the estimates of the unknowns. To cope with such problems, efficient regularization techniques are developed in the framework of numerical analysis. The counterpart of regularization in the framework of statistical inference is the use prior information.
Introduction to Applied Optimization
This text presents a multi-disciplined view of optimization, providing students and researchers with a thorough examination of algorithms, methods, and tools from diverse areas of optimization without introducing excessive theoretical detail. This second edition includes additional topics, including global optimization and a real-world case study using important concepts from each chapter.
Introduction to applied mathematics for environmental science
Introduction to Mathematics for Environmental Science evolved from the author’s 30 years’ experience teaching mathematics to graduate and advanced undergraduate students in the environmental sciences. Its basic purpose is to teach various types of mathematical structures and how they can be applied in a broad range of environmental science subfields. Derivatives and integrals, ordinary and partial differential equations, and linear and non-linear algebraic equations are the basic kinds of structures (types of mathematical models) discussed.
Introduction to Algorithms
Combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming.
Interphases and Mesophases in Polymer Crystallization II
Polymer crystallisation is a field of science whose widespread practica! and technological implications add to its scientific relevance. Unlike most molecular substances, synthetic polymers consist oflong, linear chains usually covering a broad distribution of molecular lengths. It is no surprise that only rarely may they give rise to regularly shaped crystals, if at all. As a rule, especially from the bulk state, polymers solidify as very tiny crystals interspersed in an amorphous matrix and randomly interconnected by disordered chains.This series presents critical reviews of the present and future trends in polymer and biopolymer science including chemistry, physical chemistry, physics and material science. It is adressed to ali scientists at universities and in industry who wish to keep abreast of advances in the topics covered
International steam tables : Properties of water and steam based on the industrial formulation IAPWS-IF97 : Tables, algorithms, diagrams, and CD-ROM Electronic steam tables - All of the equations of IAPWS-IF97 including a complete set of supplementary backward equations for fast calculations of heat cycles, boilers, and steam turbines
This book contains steam tables for industrial use that have been calculated using the international standard for the thermodynamic properties of water and steam, the IAPWS-IF97 formulation, and the international standards for transport and other properties. In addition, the complete set of equations of IAPWS-IF97 is presented including all supplementary backward equations adopted by IAPWS between 2001 and 2005 for fast calculations of heat cycles, boilers, and steam turbines.
Intermediate Dynamics : A Linear Algebraic Approach
As the name implies, Intermediate Dynamics: A Linear Algebraic Approach views "intermediate dynamics"--Newtonian 3-D rigid body dynamics and analytical mechanics--from the perspective of the mathematical field.
Interior Point Methods for Linear Optimization
Linear Optimization (LO) is one of the most widely applied and taught techniques in mathematics, with applications in many areas of science, commerce and industry. The dramatically increased interest in the subject is due mainly to advances in computer technology and the development of Interior Point Methods (IPMs) for LO. This book provides a unified presentation of the field. The authors present a self-contained comprehensive interior point approach to both the theory of LO and algorithms for LO (design, convergence, complexity, asymptotic behaviour and computational issues). A common thread throughout the book is the role of strictly complementary solutions, which play a crucial role in the interior point approach and distinguishes the new approach from the classical Simplex-based approach
Interfacial Convection in Multilayer Systems
This book contains a systematic investigation of the convection in systems with interfaces. For the first time, it classifies all of the known types of convective instabilities in such systems, and discusses the peculiarities of multilayer systems. The book provides an overview of the wide variety of steady and oscillatory patterns, waves, and other dynamic phenomena characteristic for multilayer fluid systems. Various physical effects, including heat and mass transfer, thermal and mechanical couplings on the interfaces, interfacial deformability, the influence of surfactants on different types of convective motions are investigated.
