Expansion In Fourier Series And Orthogonal Polynomials With Matlab
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Expansion In Fourier Series And Orthogonal Polynomials With Matlab
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Author : Mutari Hajara Ali
language : en
Publisher:
Release Date : 2017-04-04
Expansion In Fourier Series And Orthogonal Polynomials With Matlab written by Mutari Hajara Ali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-04 with categories.
Orthogonal Polynomials In Matlab
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Author : Walter Gautschi
language : en
Publisher: SIAM
Release Date : 2016-05-23
Orthogonal Polynomials In Matlab written by Walter Gautschi and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-23 with Science categories.
Techniques for generating orthogonal polynomials numerically have appeared only recently, within the last 30 or so years.?Orthogonal Polynomials in MATLAB: Exercises and Solutions?describes these techniques and related applications, all supported by MATLAB programs, and presents them in a unique format of exercises and solutions designed by the author to stimulate participation. Important computational problems in the physical sciences are included as models for readers to solve their own problems.?
Numerical Analysis Using Matlab And Excel
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Author : Steven T. Karris
language : en
Publisher: Orchard Publications
Release Date : 2007
Numerical Analysis Using Matlab And Excel written by Steven T. Karris and has been published by Orchard Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Education categories.
This text is written primarily for students/readers who have a good background of high-school algebra, geometry, trigonometry, and the fundamentals of differential and integral calculus.
Engineering Mathematics With Matlab
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Author : Won Y. Yang et. al
language : en
Publisher: Won Y. Yang
Release Date : 2019-02-01
Engineering Mathematics With Matlab written by Won Y. Yang et. al and has been published by Won Y. Yang this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-01 with Antiques & Collectibles categories.
Chapter 1: Vectors and Matrices 1.1 Vectors 1.1.1 Geometry with Vector 1.1.2 Dot Product 1.1.3 Cross Product 1.1.4 Lines and Planes 1.1.5 Vector Space 1.1.6 Coordinate Systems 1.1.7 Gram-Schmidt Orthonolization 1.2 Matrices 1.2.1 Matrix Algebra 1.2.2 Rank and Row/Column Spaces 1.2.3 Determinant and Trace 1.2.4 Eigenvalues and Eigenvectors 1.2.5 Inverse of a Matrix 1.2.6 Similarity Transformation and Diagonalization 1.2.7 Special Matrices 1.2.8 Positive Definiteness 1.2.9 Matrix Inversion Lemma 1.2.10 LU, Cholesky, QR, and Singular Value Decompositions 1.2.11 Physical Meaning of Eigenvalues/Eigenvectors 1.3 Systems of Linear Equations 1.3.1 Nonsingular Case 1.3.2 Undetermined Case - Minimum-Norm Solution 1.3.3 Overdetermined Case - Least-Squares Error Solution 1.3.4 Gauss(ian) Elimination 1.3.5 RLS (Recursive Least Squares) Algorithm Problems Chapter 2: Vector Calculus 2.1 Derivatives 2.2 Vector Functions 2.3 Velocity and Acceleration 2.4 Divergence and Curl 2.5 Line Integrals and Path Independence 2.5.1 Line Integrals 2.5.2 Path Independence 2.6 Double Integrals 2.7 Green's Theorem 2.8 Surface Integrals 2.9 Stokes' Theorem 2.10 Triple Integrals 2.11 Divergence Theorem Problems Chapter 3: Ordinary Differential Equation 3.1 First-Order Differential Equations 3.1.1 Separable Equations 3.1.2 Exact Differential Equations and Integrating Factors 3.1.3 Linear First-Order Differential Equations 3.1.4 Nonlinear First-Order Differential Equations 3.1.5 Systems of First-Order Differential Equations 3.2 Higher-Order Differential Equations 3.2.1 Undetermined Coefficients 3.2.2 Variation of Parameters 3.2.3 Cauchy-Euler Equations 3.2.4 Systems of Linear Differential Equations 3.3 Special Second-Order Linear ODEs 3.3.1 Bessel's Equation 3.3.2 Legendre's Equation 3.3.3 Chebyshev's Equation 3.3.4 Hermite's Equation 3.3.5 Laguerre's Equation 3.4 Boundary Value Problems Problems Chapter 4: Laplace Transform 4.1 Definition of the Laplace Transform 4.1.1 Laplace Transform of the Unit Step Function 4.1.2 Laplace Transform of the Unit Impulse Function 4.1.3 Laplace Transform of the Ramp Function 4.1.4 Laplace Transform of the Exponential Function 4.1.5 Laplace Transform of the Complex Exponential Function 4.2 Properties of the Laplace Transform 4.2.1 Linearity 4.2.2 Time Differentiation 4.2.3 Time Integration 4.2.4 Time Shifting - Real Translation 4.2.5 Frequency Shifting - Complex Translation 4.2.6 Real Convolution 4.2.7 Partial Differentiation 4.2.8 Complex Differentiation 4.2.9 Initial Value Theorem (IVT) 4.2.10 Final Value Theorem (FVT) 4.3 The Inverse Laplace Transform 4.4 Using of the Laplace Transform 4.5 Transfer Function of a Continuous-Time System Problems 300 Chapter 5: The Z-transform 5.1 Definition of the Z-transform 5.2 Properties of the Z-transform 5.2.1 Linearity 5.2.2 Time Shifting - Real Translation 5.2.3 Frequency Shifting - Complex Translation 5.2.4 Time Reversal 5.2.5 Real Convolution 5.2.6 Complex Convolution 5.2.7 Complex Differentiation 5.2.8 Partial Differentiation 5.2.9 Initial Value Theorem 5.2.10 Final Value Theorem 5.3 The Inverse Z-transform 5.4 Using The Z-transform 5.5 Transfer Function of a Discrete-Time System 5.6 Differential Equation and Difference Equation Problems Chapter 6: Fourier Series and Fourier Transform 6.1 Continuous-Time Fourier Series (CTFS) 6.1.1 Definition and Convergence Conditions 6.1.2 Examples of CTFS 6.2 Continuous-Time Fourier Transform (CTFT) 6.2.1 Definition and Convergence Conditions 6.2.2 (Generalized) CTFT of Periodic Signals 6.2.3 Examples of CTFT 6.2.4 Properties of CTFT 6.3 Discrete-Time Fourier Transform (DTFT) 6.3.1 Definition and Convergence Conditions 6.3.2 Examples of DTFT 6.3.3 DTFT of Periodic Sequences 6.3.4 Properties of DTFT 6.4 Discrete Fourier Transform (DFT) 6.5 Fast Fourier Transform (FFT) 6.5.1 Decimation-in-Time (DIT) FFT 6.5.2 Decimation-in-Frequency (DIF) FFT 6.5.3 Computation of IDFT Using FFT Algorithm 6.5.4 Interpretation of DFT Results 6.6 Fourier-Bessel/Legendre/Chebyshev/Cosine/Sine Series 6.6.1 Fourier-Bessel Series 6.6.2 Fourier-Legendre Series 6.6.3 Fourier-Chebyshev Series 6.6.4 Fourier-Cosine/Sine Series Problems Chapter 7: Partial Differential Equation 7.1 Elliptic PDE 7.2 Parabolic PDE 7.2.1 The Explicit Forward Euler Method 7.2.2 The Implicit Forward Euler Method 7.2.3 The Crank-Nicholson Method 7.2.4 Using the MATLAB Function 'pdepe()' 7.2.5 Two-Dimensional Parabolic PDEs 7.3 Hyperbolic PDES 7.3.1 The Explict Central Difference Method 7.3.2 Tw-Dimensional Hyperbolic PDEs 7.4 PDES in Other Coordinate Systems 7.4.1 PDEs in Polar/Cylindrical Coordinates 7.4.2 PDEs in Spherical Coordinates 7.5 Laplace/Fourier Transforms for Solving PDES 7.5.1 Using the Laplace Transform for PDEs 7.5.2 Using the Fourier Transform for PDEs Problems Chapter 8: Complex Analysis 509 8.1 Functions of a Complex Variable 8.1.1 Complex Numbers and their Powers/Roots 8.1.2 Functions of a Complex Variable 8.1.3 Cauchy-Riemann Equations 8.1.4 Exponential and Logarithmic Functions 8.1.5 Trigonometric and Hyperbolic Functions 8.1.6 Inverse Trigonometric/Hyperbolic Functions 8.2 Conformal Mapping 8.2.1 Conformal Mappings 8.2.2 Linear Fractional Transformations 8.3 Integration of Complex Functions 8.3.1 Line Integrals and Contour Integrals 8.3.2 Cauchy-Goursat Theorem 8.3.3 Cauchy's Integral Formula 8.4 Series and Residues 8.4.1 Sequences and Series 8.4.2 Taylor Series 8.4.3 Laurent Series 8.4.4 Residues and Residue Theorem 8.4.5 Real Integrals Using Residue Theorem Problems Chapter 9: Optimization 9.1 Unconstrained Optimization 9.1.1 Golden Search Method 9.1.2 Quadratic Approximation Method 9.1.3 Nelder-Mead Method 9.1.4 Steepest Descent Method 9.1.5 Newton Method 9.2 Constrained Optimization 9.2.1 Lagrange Multiplier Method 9.2.2 Penalty Function Method 9.3 MATLAB Built-in Functions for Optimization 9.3.1 Unconstrained Optimization 9.3.2 Constrained Optimization 9.3.3 Linear Programming (LP) 9.3.4 Mixed Integer Linear Programing (MILP) Problems Chapter 10: Probability 10.1 Probability 10.1.1 Definition of Probability 10.1.2 Permutations and Combinations 10.1.3 Joint Probability, Conditional Probability, and Bayes' Rule 10.2 Random Variables 10.2.1 Random Variables and Probability Distribution/Density Function 10.2.2 Joint Probability Density Function 10.2.3 Conditional Probability Density Function 10.2.4 Independence 10.2.5 Function of a Random Variable 10.2.6 Expectation, Variance, and Correlation 10.2.7 Conditional Expectation 10.2.8 Central Limit Theorem - Normal Convergence Theorem 10.3 ML Estimator and MAP Estimator 653 Problems
Mathematical Modeling And Computation In Finance With Exercises And Python And Matlab Computer Codes
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Author : Cornelis W Oosterlee
language : en
Publisher: World Scientific
Release Date : 2019-10-29
Mathematical Modeling And Computation In Finance With Exercises And Python And Matlab Computer Codes written by Cornelis W Oosterlee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-29 with Business & Economics categories.
This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.
Radar Systems Analysis And Design Using Matlab
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Author : Bassem R. Mahafza
language : en
Publisher: CRC Press
Release Date : 2022-03-29
Radar Systems Analysis And Design Using Matlab written by Bassem R. Mahafza and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-29 with Technology & Engineering categories.
The first edition of this ground-breaking and widely used book introduced a comprehensive textbook on radar systems analysis and design providing hands-on experience facilitated by its companion MATLAB® software. The book very quickly turned into a bestseller. Based on feedback provided by several users and drawing from the author's own teaching experience, the 4th edition adopts a new approach. The presentation in this edition takes the reader on a scientific journey whose major landmarks comprise the different radar sub-systems and components. Along the way, the different relevant radar subsystems are analyzed and discussed in great level of detail. Understanding the radar signal types and their associated radar signal processing techniques are key to understating how radar systems function. Each chapter provides the necessary mathematical and analytical coverage required for a sound understanding of radar theory. Additionally, dedicated MATLAB® functions/programs enhance the understanding of the theory and establish a means to perform radar system analysis and design trades. The software provides users with numerous varieties of graphical outputs. Additionally, a complete set of MATLAB® code that generates all plot and graphs found within the pages of this textbook are also available. All companion MATLAB® code can be downloaded from the book’s web page. The 4th Edition: •Takes advantage of the new features offered by MATLAB® 2021 release •Brings the text to a current state of the art •Incorporates much of the feedback received from users using this book as a text and from practicing engineers; accordingly, several chapters have been rewritten •Presents unique topics not found in other books •Maintains a comprehensive and exhaustive presentation •Restructures the presentation to be more convenient for course use. •Provides a post-course reference for engineering students as they enter the field •Offers a companion solutions manual for instructors The 4th edition will serve as a valuable tool to students and radar engineers by helping them better analyze and understand the many topics of radar systems. This book is written primarily as a graduate-level textbook, although parts of it can be used as a senior level course. A companion solutions manual has been developed for use by instructors.
Numerical Fourier Analysis
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Author : Gerlind Plonka
language : en
Publisher: Springer Nature
Release Date : 2023-11-08
Numerical Fourier Analysis written by Gerlind Plonka and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-08 with Mathematics categories.
New technological innovations and advances in research in areas such as spectroscopy, computer tomography, signal processing, and data analysis require a deep understanding of function approximation using Fourier methods. To address this growing need, this monograph combines mathematical theory and numerical algorithms to offer a unified and self-contained presentation of Fourier analysis. The first four chapters of the text serve as an introduction to classical Fourier analysis in the univariate and multivariate cases, including the discrete Fourier transforms, providing the necessary background for all further chapters. Next, chapters explore the construction and analysis of corresponding fast algorithms in the one- and multidimensional cases. The well-known fast Fourier transforms (FFTs) are discussed, as well as recent results on the construction of the nonequispaced FFTs, high-dimensional FFTs on special lattices, and sparse FFTs. An additional chapter is devoted to discrete trigonometric transforms and Chebyshev expansions. The final two chapters consider various applications of numerical Fourier methods for improved function approximation, including Prony methods for the recovery of structured functions. This new edition has been revised and updated throughout, featuring new material on a new Fourier approach to the ANOVA decomposition of high-dimensional trigonometric polynomials; new research results on the approximation errors of the nonequispaced fast Fourier transform based on special window functions; and the recently developed ESPIRA algorithm for recovery of exponential sums, among others. Numerical Fourier Analysis will be of interest to graduate students and researchers in applied mathematics, physics, computer science, engineering, and other areas where Fourier methods play an important role in applications.
Signals And Systems
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Author : Steven T. Karris
language : en
Publisher: Orchard Publications
Release Date : 2012
Signals And Systems written by Steven T. Karris and has been published by Orchard Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
This text is primarily written for junior and senior undergraduates majoring in electrical and computer engineering. You will need this text if you are a student or working professional seeking to learn and/or review the basics of the Laplace and Z-transforms, the Fast Fourier Transform (FFT), state variables, design of analog and digital filters, window functions, cross correlation, auto correlation, and an example of a describing function. Contains many real-world examples completely solved in detail and verified with MATLAB script and Simulink models.
Numerical Analysis Of Partial Differential Equations Using Maple And Matlab
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Author : Martin J. Gander
language : en
Publisher: SIAM
Release Date : 2018-08-06
Numerical Analysis Of Partial Differential Equations Using Maple And Matlab written by Martin J. Gander and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-06 with Science categories.
This book provides an elementary yet comprehensive introduction to the numerical solution of partial differential equations (PDEs). Used to model important phenomena, such as the heating of apartments and the behavior of electromagnetic waves, these equations have applications in engineering and the life sciences, and most can only be solved approximately using computers.? Numerical Analysis of Partial Differential Equations Using Maple and MATLAB provides detailed descriptions of the four major classes of discretization methods for PDEs (finite difference method, finite volume method, spectral method, and finite element method) and runnable MATLAB? code for each of the discretization methods and exercises. It also gives self-contained convergence proofs for each method using the tools and techniques required for the general convergence analysis but adapted to the simplest setting to keep the presentation clear and complete. This book is intended for advanced undergraduate and early graduate students in numerical analysis and scientific computing and researchers in related fields. It is appropriate for a course on numerical methods for partial differential equations.
An Introduction To Partial Differential Equations With Matlab
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Author : Matthew P. Coleman
language : en
Publisher: CRC Press
Release Date : 2024-08-01
An Introduction To Partial Differential Equations With Matlab written by Matthew P. Coleman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-01 with Mathematics categories.
The first two editions of An Introduction to Partial Differential Equations with MATLAB® gained popularity among instructors and students at various universities throughout the world. Plain mathematical language is used in a friendly manner to provide a basic introduction to partial differential equations (PDEs). Suitable for a one- or two-semester introduction to PDEs and Fourier series, the book strives to provide physical, mathematical, and historical motivation for each topic. Equations are studied based on method of solution, rather than on type of equation. This third edition of this popular textbook updates the structure of the book by increasing the role of the computational portion, compared to previous editions. The redesigned content will be extremely useful for students of mathematics, physics, and engineering who would like to focus on the practical aspects of the study of PDEs, without sacrificing mathematical rigor. The authors have maintained flexibility in the order of topics. In addition, students will be able to use what they have learned in some later courses (for example, courses in numerical analysis, optimization, and PDE-based programming). Included in this new edition is a substantial amount of material on reviewing computational methods for solving ODEs (symbolically and numerically), visualizing solutions of PDEs, using MATLAB®'s symbolic programming toolbox, and applying various schemes from numerical analysis, along with suggestions for topics of course projects. Students will use sample MATLAB® or Python codes available online for their practical experiments and for completing computational lab assignments and course projects.