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Author: Won Y. Yang et. al
Publisher: Won Y. Yang
ISBN: 1138059331
Category : Antiques & Collectibles
Languages : en
Pages : 752
Get Book Here
Book Description
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
Author: Won Y. Yang et. al
Publisher: Won Y. Yang
ISBN: 1138059331
Category : Antiques & Collectibles
Languages : en
Pages : 752
Get Book Here
Book Description
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
Author: Dean G. Duffy
Publisher: CRC Press
ISBN: 1000514269
Category : Mathematics
Languages : en
Pages : 616
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Book Description
In the four previous editions the author presented a text firmly grounded in the mathematics that engineers and scientists must understand and know how to use. Tapping into decades of teaching at the US Navy Academy and the US Military Academy and serving for twenty-five years at (NASA) Goddard Space Flight, he combines a teaching and practical experience that is rare among authors of advanced engineering mathematics books. This edition offers a smaller, easier to read, and useful version of this classic textbook. While competing textbooks continue to grow, the book presents a slimmer, more concise option. Instructors and students alike are rejecting the encyclopedic tome with its higher and higher price aimed at undergraduates. To assist in the choice of topics included in this new edition, the author reviewed the syllabi of various engineering mathematics courses that are taught at a wide variety of schools. Due to time constraints an instructor can select perhaps three to four topics from the book, the most likely being ordinary differential equations, Laplace transforms, Fourier series and separation of variables to solve the wave, heat, or Laplace's equation. Laplace transforms are occasionally replaced by linear algebra or vector calculus. Sturm-Liouville problem and special functions (Legendre and Bessel functions) are included for completeness. Topics such as z-transforms and complex variables are now offered in a companion book, Advanced Engineering Mathematics: A Second Course by the same author. MATLAB is still employed to reinforce the concepts that are taught. Of course, this Edition continues to offer a wealth of examples and applications from the scientific and engineering literature, a highlight of previous editions. Worked solutions are given in the back of the book.
Author: Reza Malek-Madani
Publisher: Addison Wesley
ISBN:
Category : Computers
Languages : en
Pages : 612
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Book Description
See previous listing for contents.
Author: Dean G. Duffy
Publisher: CRC Press
ISBN: 1000551253
Category : Mathematics
Languages : en
Pages : 466
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Book Description
Through four previous editions of Advanced Engineering Mathematics with MATLAB, the author presented a wide variety of topics needed by today's engineers. The fifth edition of that book, available now, has been broken into two parts: topics currently needed in mathematics courses and a new stand-alone volume presenting topics not often included in these courses and consequently unknown to engineering students and many professionals. The overall structure of this new book consists of two parts: transform methods and random processes. Built upon a foundation of applied complex variables, the first part covers advanced transform methods, as well as z-transforms and Hilbert transforms--transforms of particular interest to systems, communication, and electrical engineers. This portion concludes with Green's function, a powerful method of analyzing systems. The second portion presents random processes--processes that more accurately model physical and biological engineering. Of particular interest is the inclusion of stochastic calculus. The author continues to offer a wealth of examples and applications from the scientific and engineering literature, a highlight of his previous books. As before, theory is presented first, then examples, and then drill problems. Answers are given in the back of the book. This book is all about the future: The purpose of this book is not only to educate the present generation of engineers but also the next. "The main strength is the text is written from an engineering perspective. The majority of my students are engineers. The physical examples are related to problems of interest to the engineering students." --Lea Jenkins, Clemson University
Author: Dingyu Xue
Publisher: CRC Press
ISBN: 1498757782
Category : Mathematics
Languages : en
Pages : 589
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Book Description
Scientific Computing with MATLAB®, Second Edition improves students’ ability to tackle mathematical problems. It helps students understand the mathematical background and find reliable and accurate solutions to mathematical problems with the use of MATLAB, avoiding the tedious and complex technical details of mathematics. This edition retains the structure of its predecessor while expanding and updating the content of each chapter. The book bridges the gap between problems and solutions through well-grouped topics and clear MATLAB example scripts and reproducible MATLAB-generated plots. Students can effortlessly experiment with the scripts for a deep, hands-on exploration. Each chapter also includes a set of problems to strengthen understanding of the material.
Author: Jon H. Davis
Publisher: Springer Science & Business Media
ISBN: 9780817643317
Category : Mathematics
Languages : en
Pages : 744
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Book Description
Broadly organized around the applications of Fourier analysis, "Methods of Applied Mathematics with a MATLAB Overview" covers both classical applications in partial differential equations and boundary value problems, as well as the concepts and methods associated to the Laplace, Fourier, and discrete transforms. Transform inversion problems are also examined, along with the necessary background in complex variables. A final chapter treats wavelets, short-time Fourier analysis, and geometrically-based transforms. The computer program MATLAB is emphasized throughout, and an introduction to MATLAB is provided in an appendix. Rich in examples, illustrations, and exercises of varying difficulty, this text can be used for a one- or two-semester course and is ideal for students in pure and applied mathematics, physics, and engineering.
Author: Rajinder Kumar Jain
Publisher: Alpha Science International, Limited
ISBN: 9781842653128
Category : Engineering mathematics
Languages : en
Pages : 0
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Book Description
This work is based on the experience and notes of the authors while teaching mathematics courses to engineering students at the Indian Institute of Technology, New Delhi. It covers syllabi of two core courses in mathematics for engineering students.
Author: Steven L. Brunton
Publisher: Cambridge University Press
ISBN: 1009098489
Category : Computers
Languages : en
Pages : 615
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Book Description
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author: Jose Miguel David Baez-Lopez
Publisher: CRC Press
ISBN: 1351856162
Category : Mathematics
Languages : en
Pages : 345
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Book Description
The purpose of this handbook is to allow users to learn and master the mathematics software package MATLAB®, as well as to serve as a quick reference to some of the most used instructions in the package. A unique feature of this handbook is that it can be used by the novice and by experienced users alike. For experienced users, it has four chapters with examples and applications in engineering, finance, physics, and optimization. Exercises are included, along with solutions available for the interested reader on the book’s web page. These exercises are a complement for the interested reader who wishes to get a deeper understanding of MATLAB. Features Covers both MATLAB and introduction to Simulink Covers the use of GUIs in MATLAB and Simulink Offers downloadable examples and programs from the handbook’s website Provides an introduction to object oriented programming using MATLAB Includes applications from many areas Includes the realization of executable files for MATLAB programs and Simulink models
Author: Tom Lyche
Publisher: Springer
ISBN: 366243511X
Category : Mathematics
Languages : en
Pages : 377
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Book Description
Designed to provide tools for independent study, this book contains student-tested mathematical exercises joined with MATLAB programming exercises. Most chapters open with a review followed by theoretical and programming exercises, with detailed solutions provided for all problems including programs. Many of the MATLAB exercises are presented as Russian dolls: each question improves and completes the previous program and results are provided to validate the intermediate programs. The book offers useful MATLAB commands, advice on tables, vectors, matrices and basic commands for plotting. It contains material on eigenvalues and eigenvectors and important norms of vectors and matrices including perturbation theory; iterative methods for solving nonlinear and linear equations; polynomial and piecewise polynomial interpolation; Bézier curves; approximations of functions and integrals and more. The last two chapters considers ordinary differential equations including two point boundary value problems, and deal with finite difference methods for some partial differential equations. The format is designed to assist students working alone, with concise Review paragraphs, Math Hint footnotes on the mathematical aspects of a problem and MATLAB Hint footnotes with tips on programming.
