Xcos is a very powerful and open source block-based modeling and simulation system for dynamical systems. Its capabilities are comparable to commercially available block-based modeling and simulation tools, including Simulink(R), one of the most popular commercial tool. Xcos is useful for modeling continuous and discrete dynamical systems. Further, it provides facilities to seamlessly integrate continuous and discrete components in a single model, making it capable to handle hybrid dynamical systems. Xcos provides a modular approach to model complex dynamical systems using a block diagram editor. Xcos contains a rich library of commonly used blocks, arranged in various palettes for the convenience of searching them, for elementary operations needed to construct models of many dynamical systems. These blocks can be dragged and dropped into the model editor to create a simulation model. For advanced users, Xcos provides facilities to create new blocks and to create their own libraries to further extend the capabilities of Xcos. Since Xcos is available free of cost to everyone across the globe and is continuously upgraded by a strong team of open source developers, it is suitable for all undergraduate students, researchers, professors and professionals in any field of Science and Engineering. Further, many commercial developers are also using it to reduce their project cost and has reported many successful applications.Starting from the basic concepts, the book gradually builds advanced concepts, making it suitable for freshmen and professionals. The Xcos models of all the examples included in this book are available at https: //github.com/arvindrachna/Introduction_to_Xcos. The book consists of the following 15 chapters: Chapter 1: Introduction to XcosChapter 2: Sources PaletteChapter 3: Sinks PaletteChapter 4: Mathematical Operations PaletteChapter 5: Matrix Operation PaletteChapter 6: Signal Routing PaletteChapter 7: Event Handling PaletteChapter 8: Integer PaletteChapter 9: Continuous Time Systems PaletteChapter 10: Discrete Time Systems PaletteChapter 11: Discontinuities PaletteChapter 12: Port and Subsystem PaletteChapter 13: User-Defined Functions Palette and Construction of a New BlockChapter 14: Illustrative Solutions of Differential Equations using XcosChapter 15: Modelica based blocks in Xcos

Scilab and its Scicos block diagram graphical editor, with a special emphasis on modeling and simulation tools. The first part is a detailed Scilab tutorial, and the second is dedicated to modeling and simulation of dynamical systems in Scicos. The concepts are illustrated through numerous examples, and all code used in the book is available to the reader.

Familiarize yourself with Scilab using this concise, practical tutorial that is focused on writing code to learn concepts. Starting from the basics, this book covers array-based computing, plotting, and working with files in Scilab. Introduction to Scilab is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation. In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you’ll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts. After reading this book, you will come away with sample code that can be re-purposed and applied to your own projects using Scilab. What You'll Learn Apply sample code to your engineering or science problems Work with Scilab arrays, functions, and loops Use Scilab’s plotting functions for data visualization Solve numerical computing and computational engineering problems with Scilab Who This Book Is For Engineers, scientists, researchers, and students who are new to Scilab. Some prior programming experience would be helpful but not required.

Intended for an honors calculus course or for an introduction to analysis, this is an ideal text for undergraduate majors since it covers rigorous analysis, computational dexterity, and a breadth of applications. The book contains many remarkable features: * complete avoidance of /epsilon-/delta arguments by using sequences instead * definition of the integral as the area under the graph, while area is defined for every subset of the plane * complete avoidance of complex numbers * heavy emphasis on computational problems * applications from many parts of analysis, e.g. convex conjugates, Cantor set, continued fractions, Bessel functions, the zeta functions, and many more * 344 problems with solutions in the back of the book.

Scilab and its Scicos block diagram graphical editor, with a special emphasis on modeling and simulation tools. The first part is a detailed Scilab tutorial, and the second is dedicated to modeling and simulation of dynamical systems in Scicos. The concepts are illustrated through numerous examples, and all code used in the book is available to the reader.

Our understanding of the fundamental processes of the natural world is based to a large extent on partial differential equations (PDEs). The second edition of Partial Differential Equations provides an introduction to the basic properties of PDEs and the ideas and techniques that have proven useful in analyzing them. It provides the student a broad perspective on the subject, illustrates the incredibly rich variety of phenomena encompassed by it, and imparts a working knowledge of the most important techniques of analysis of the solutions of the equations. In this book mathematical jargon is minimized. Our focus is on the three most classical PDEs: the wave, heat and Laplace equations. Advanced concepts are introduced frequently but with the least possible technicalities. The book is flexibly designed for juniors, seniors or beginning graduate students in science, engineering or mathematics.

As an excellent, easy-to-understand introduction to analysis, this book involves rigorous analysis, computational dexterity, and a breadth of applications, making it ideal for undergraduate majors. The book contains many remarkable features, including a heavy emphasis on computational problems and applications from many parts of analysis. The work completely avoids treating complex numbers. Nearly 350 problems with solutions are included in the back of the book.