【新书推荐】【2020】基于Simulink进行实用的MATLAB建模:常微分方程和偏微分方程的编程与仿真

【新书推荐】【2020】基于Simulink进行实用的MATLAB建模:常微分方程和偏微分方程的编程与仿真_第1张图片

利用MATLAB的常微分方程(ODE)和偏微分方程(PDE)软件包的基本工具和实用功能,通过交互式示例和案例分析进行说明和演示。

Employ the essential and hands-on tools and functions of MATLAB’s ordinary differential equation (ODE) and partial differential equation (PDE) packages, which are explained and demonstrated via interactive examples and case studies.

本书包含了许多通过m-files/scripts和Simulink模型进行的模拟和解决的问题,这些模型可以帮助您学习使用ODEs和PDEs的更困难、更复杂问题的编程和建模。

This book contains dozens of simulations and solved problems via m-files/scripts and Simulink models which help you to learn programming and modeling of more difficult, complex problems that involve the use of ODEs and PDEs.

在解决需要和使用微分方程的更复杂的工程和科学计算问题的同时,使用许多内置工具和MATLAB/Simulink功能,您将更加高效。

You’ll become efficient with many of the built-in tools and functions of MATLAB/Simulink while solving more complex engineering and scientific computing problems that require and use differential equations.

用Simulink进行实际的MATLAB建模,解释了编程和建模的各种实际问题。

Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling.

阅读并使用本书之后,您将熟练地使用MATLAB,并将本书示例中的源代码作为您自己的数据科学或工程项目的模板。

After reading and using this book, you’ll be proficient at using MATLAB and applying the source code from the book’s examples as templates for your own projects in data science or engineering.

使用MATLAB和Simulink学习建模复杂的问题,获得使用ODE和PDE进行MATLAB编程和建模的要点

What You Will Learn Model complex problems using MATLAB and Simulink Gain the programming and modeling essentials of MATLAB using ODEs and PDEs

使用数值方法解一阶和二阶ODE

Use numerical methods to solve 1st and 2nd order ODEs

求解刚性、高阶、耦合和隐式ODE

Solve stiff, higher order, coupled, and implicit ODEs

用数值方法求解一阶和二阶线性偏微分方程

Employ numerical methods to solve 1st and 2nd order linear PDEs

求解刚性、高阶、耦合和隐式偏微分方程

Solve stiff, higher order, coupled, and implicit PDEs

本书面向工程师、程序员、数据科学家和工程、应用/工业数学、数据科学和科学计算专业的学生。

This Book Is For Engineers, programmers, data scientists, and students majoring in engineering, applied/industrial math, data science, and scientific computing.

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