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.

Scilab is a very powerful, free and open-source software package for scientific and technical computation, visualization and programming. It includes a large number of general purpose and specialized functions, using state of the art algorithms, for numerical computation. These functions are organized in libraries called toolboxes that cover areas such as simulation, optimization, image processing, control and signal processing. With easy to use high level programming language and huge library of functions, Scilab reduces considerably the burden of programming for scientific and technical applications. It can also be interactively used as a very powerful scientific calculator. Since Scilab 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.This book is written following several years of teaching the software to our students in introductory courses in numerical methods. The basic objective to write this book is to teach Scilab in a friendly, non-intimidating fashion, without any previous programming experience. Therefore, the book is written in simple language with many sample problems in mathematics, science, and engineering. Starting from the basic concepts, the book gradually builds advanced concepts, making it suitable for freshmen and professionals. The source codes of all the examples presented in this book can be downloaded from https://github.com/arvindrachna/Introduction_to_ScilabFor promoting outcome based learning, each chapter of the book starts with chapter objectives and lucidly introduces the basic concepts, with sample examples, to achieve those objectives. Each chapter concludes with a summary and a list of key terms to recapitulate the learned concepts. Finally, the chapter ends with exercise problems so as students can apply the concepts learned in the chapter.The book consists of seven chapters. The first chapter gives a focused introduction to Scilab and explains how one can install the software on ones machine. The second chapter introduces the core concepts of Scilab, a matrix based technical computing environment. This chapter also introduces how the software can be used in its interactive mode to solve scientific and technical problems. The third chapter introduces how to create and manipulate vectors and matrices in Scilab. It also introduces array and matrix operators. The fourth chapter explains how polynomials can be processed in Scilab. Polynomial operations, differentiation and integration are also introduced. The fifth chapter explains graphics capabilities of Scilab. Various 2D and 3D graphics functions are explained in this chapter. The sixth chapter is focused on the programming capabilities of the software. Various programming constructs are explained with examples. The last chapter explains basic numerical methods and how to create Scilab programs for them. This chapter helps students to apply the learned concepts to actual numerical method problems. The book ends with an appendix of commonly used Scilab commands and functions.Table of Contents1Introduction to Scilab2Basics of Scilab3Vectors and Matrices4Polynomials5Scilab Graphics6Programming in Scilab7Numerical Methods Using Scilab8Appendix I : Commonly Used Scilab Functions

Supplementary files run on UNIX and Windows 95/98/NT

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.

Simulation of ODE/PDE Models with MATLAB®, OCTAVE and SCILAB shows the reader how to exploit a fuller array of numerical methods for the analysis of complex scientific and engineering systems than is conventionally employed. The book is dedicated to numerical simulation of distributed parameter systems described by mixed systems of algebraic equations, ordinary differential equations (ODEs) and partial differential equations (PDEs). Special attention is paid to the numerical method of lines (MOL), a popular approach to the solution of time-dependent PDEs, which proceeds in two basic steps: spatial discretization and time integration. Besides conventional finite-difference and element techniques, more advanced spatial-approximation methods are examined in some detail, including nonoscillatory schemes and adaptive-grid approaches. A MOL toolbox has been developed within MATLAB®/OCTAVE/SCILAB. In addition to a set of spatial approximations and time integrators, this toolbox includes a collection of application examples, in specific areas, which can serve as templates for developing new programs. Simulation of ODE/PDE Models with MATLAB®, OCTAVE and SCILAB provides a practical introduction to some advanced computational techniques for dynamic system simulation, supported by many worked examples in the text, and a collection of codes available for download from the book’s page at www.springer.com. This text is suitable for self-study by practicing scientists and engineers and as a final-year undergraduate course or at the graduate level.

Arduino and Scilab based Projects provides information ranging from the basics to advanced knowledge of Arduino and its interfacing with input/output devices (display devices, actuators, sensors), communication modules (RF modem, Zigbee) and Scilab. It also provides embedded system based on Arduino with simulation, programming and interfacing with Scilab, Arduino interfacing with Scilab with and without Arduino 1.1 packages. Chapters are arranged in an easy-to-understand sequence that enhances the learning experience for readers. Descriptions of real time project prototypes with programming and simulation of Arduino and Scilab.