Financial Instruments Toolbox: Dual curve construction, functions to compute credit exposure and exposure profile, and Black's model pricing of caps, floors, and swaptions.Econometrics Toolbox: State-space models, self-calibrating Kalman filter with missing data, and performance enhancements for ARIMA/GARCH models.Image Processing Toolbox: C-code generation for 25 functions with MATLAB Coder, and GPU acceleration for 5 functions.Statistics Toolbox: Repeated measures modelling for data with multiple measurements per subject.Optimization Toolbox: Mixed-integer linear programming (MILP) solver.MATLAB: Raspberry Pi and webcam hardware support packages.R2014a includes new releases of MATLAB and Simulink, and updates and bug fixes to 81 other products. 9.MathWorks today announced Release 2014a (R2014a) of its MATLAB and Simulink product families.9.4.5 The Symmetric and Non-Negative Least Squares Method.9.4 Solving Equations and Systems of Equations.9.1 Expanding, Simplifying and Factoring Algebraic Expressions.Chapter 9: Algebraic Expressions, Polynomials, Equations and Systems.8.7 Matrix Operations with Real and Complex Variables.8.6.4 Specific Functions of a Complex Matrix Variable.8.6.3 Exponential and Logarithmic Functions of a Complex Matrix Variable.8.6.2 Hyperbolic Functions of a Complex Matrix Variable.8.6.1 Trigonometric Functions of a Complex Matrix Variable.8.6 General Functions with Complex Matrix Arguments.8.5 Basic Functions with Complex Matrix Arguments.8.4 Basic Functions with Complex Vector Arguments.8.3 Specific Functions of a Complex Variable.8.2.3 Exponential and Logarithmic Functions of a Complex Variable.8.2.2 Hyperbolic Functions of a Complex Variable.8.2.1 Trigonometric Functions of a Complex Variable.8.2 General Functions of a Complex Variable.Chapter 8: Optimization of Functions of Complex Variables.Spherical, Cylindrical and Rectangular Coordinates.7.12 Series Expansions in Several Variables.7.5 Maxima and Minima of Functions of Several Variables.7.4 Differentiation of Functions of Several Variables.Tangents, Asymptotes, Extreme Points and Turning Points Chapter 7: Differentiation in one and Several Variables.6.4.3 Linear Non- Negative Least Squares Problems.6.4.2 Non- Linear Least Squares Problems.6.4.1 Conditional Least Squares Problems.6.3.1 Solving Equations and Systems of Equations.6.2.7 Semi-Infinitely Constrained Minimization.6.2.6 Minimum Optimization: fminsearch and fminuc.6.2.4 Minimax Optimization: fminimax and fminuc.6.2.3 Non-Linear Minimization with Restrictions.6.2.2 Non-Linear Scalar Minimization With Boundary Conditions.Chapter 6: Optimization Techniques Via The Optimization Toolbox.5.1 Symbolic Equations and Systems of Equations.Chapter 5: Optimization Using Symbolic Computation.4.1.3 Schröder’s Method for Solving the Equation f(x) = 0.4.1.2 Newton’s Method for Solving the Equation f(x) = 0.4.1.1 The Fixed Point Method for Solving x = g(x).Chapter 4: Optimization by Numerical Methods: Solving Equations.3.1 Solutions of Equations and Systems of Equations.Chapter 3: Basic MATLAB Functions for Linear and Non-Linear Optimization.2.1.10 Multidimensional Array Functions.2.1.9 Functions Relating to Arrays of Cells.2.1.6 Flow Control: FOR, WHILE and IF ELSEIF Loops.1.1.5 Publication of Results and Distribution of Applications. 1.1.1 Developing Algorithms and Applications.Chapter 1: Introducing MATLAB and the MATLAB Working Environment.A wide range of exercises and examples are included, illustrating the most widely used optimization methods. The central part of the book is dedicated to MATLABs Optimization Toolbox, which implements state-of-the-art algorithms for solving multiobjective problems, non-linear minimization with boundary conditions and restrictions, minimax optimization, semi-infinitely constrained minimization and linear and quadratic programming. It begins by introducing the MATLAB environment and the structure of MATLAB programming before moving on to the mathematics of optimization. MATLAB Optimization Techniques introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. MATLAB is a high-level language and environment for numerical computation, visualization, and programming.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |