MATHEMATICAL METHODS WITH MATLAB

The objective of this book is to present the work with mathematical methods through MATLAB, both numerical analysis methods and symbolic calculation methods. The book begins by explaining the MATLAB language including working with operators, variables, and functions. Below are the elements of the MATLAB programming language including working with m-files, scripts, and control-flow statements. An essential part of the content is the functions and algorithms for numerical analysis in MATLAB, including solving equations and systems, optimization, differentiation, integration, ordinary differential equations, and partial differential equations. Finally, the symbolic calculation methods are developed in MATLAB, including variables, functions, mathematical analysis, limits, continuity, numerical series, power series, derivatives, integrals, differential equations and linear algebra methods.or intrinsic structures in input data. Supervised learning uses classification and regression techniques to develop predictive models. MATLAB has the tool Deep Learning Toolbox (Neural Network Toolbox for versions before 18) that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, pattern recognition, dimensionality reduction, time-series forecasting, dynamic system modeling and control and most machine learning techniques. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox. Read more