“…At the end of the book, you will have a good knowledge of all the elements needed to manage data from every possible source, from high-end scientific instruments to Arduino boards, from PHP SQL databases queries to simple HTML tables, and from Matlab calculations to reports in Excel. You will be able to provide cutting-edge charts exploiting the growing power of modern browsers. …”

“…Provides insight into all necessary components of algorithmic trading including: transaction cost analysis, market impact estimation, risk modeling and optimization, and advanced examination of trading algorithms and corresponding data requirements Increased coverage of essential mathematics, probability and statistics, machine learning, predictive analytics, and neural networks, and applications to trading and finance Advanced multiperiod trade schedule optimization and portfolio construction techniques Techniques to decode broker-dealer and third-party vendor models Methods to incorporate TCA into proprietary alpha models and portfolio optimizers TCA library for numerous software applications and programming languages including: MATLAB, Excel Add-In, Python, Java, C/C++, .Net, Hadoop, and as standalone .EXE and .COM applications…”

“…Lastly, it provides performance comparisons, results, and MATLAB codes and offers readers practical implementation designs for SMTs. …”

“…Offers elaborate explanations of basic finite element procedures Delivers clear explanations of the capabilities and limitations of finite element analysis Includes application examples and tutorials for commercial finite element software, such as MATLAB, ANSYS, ABAQUS and NASTRAN Provides numerous examples and exercise problems Comes with a complete solution manual and results of several engineering design projects Introduction to Finite Element Analysis and Design, 2nd Edition is an excellent text for junior and senior level undergraduate students and beginning graduate students in mechanical, civil, aerospace, biomedical engineering, industrial engineering and engineering mechanics…”

“…He is the author of Introduction to Numerical Electrostatics Using MATLAB from Wiley…”

“…This part is essentially self-contained, although it assumes some ability to program in Fortran or C and/or the ability to use R/S-Plus or Matlab. This part of the book can be used as the text for a course in statistical computing, or as a supplementary text for various courses that emphasize computations. …”

“…Parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis Contains algorithms that are applicable to real time systems Introduces fast and simple adaptation rules for type-1 and type-2 fuzzy neural networks Number of case studies both in identification and control Provides MATLAB® codes for some algorithms in the book…”

“…Plentiful teaching supplements are available, including an Instructor’s Manual and PowerPoint slides, as well as MATLAB programming assignments that require students to code algorithms in an effort to provide a deeper understanding of the material. …”

“…What You Will Learn Gather, cleanse, access, and map data to a visual framework Recognize which visualization method is applicable and learn best practices for data visualization Get acquainted with reader-driven narratives and author-driven narratives and the principles of perception Understand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with it Explore with various visualization choices how Python can be very useful in computation in the field of finance and statistics Get to know why Python is the second choice after Java, and is used frequently in the field of machine learning Compare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.js Discover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. …”

“…Links to additional software, including POLYMATHTM, MatlabTM, Wolfram MathematicaTM, AspenTechTM, and COMSOLTM. …”

“…Many recipes include examples demonstrating actual applications, and most sections rely on widely used MATLAB tools. DSP fundamentals: ideal, natural, and instantaneous sampling; delta functions; physical signal reconstruction; and more Fourier Analysis: Fourier series and transforms; discrete-time and discrete Fourier transforms; signal truncation; DFT leakage and resolution Fast Fourier transforms: decimation in time and frequency; prime factor algorithms; and fast convolution Window techniques: sinusoidal analysis; window characteristics and choices; Kaiser windows; and more Classical spectrum analysis: unmodified and modified periodograms; Bartlett’s and Welch’s periodograms; and periodogram performance FIR filters: design options; linear-phase FIR filters; periodicities; basic and Kaiser window methods; and the Parks-McClellan algorithm Analog prototype filters: Laplace transforms; characterization; and Butterworth, Chebyshev, elliptic, and Bessel filters z-Transform analysis: computation and transforms using partial fraction expansion IIR filters: design options; impulse invariance methods; and bilinear transformation Multirate signal processing: decimation and interpolation fundamentals; multistage and polyphase decimat..…”

“…The included CD features several computer programs used and described in this book for computing the per-unit-length parameter matrices and a subcircuit model for three-conductor lines, as well as two MATLAB programs for computing the Fourier components of a digital waveform and two versions of PSPICE.This book is intended as a textbook for a senior/first-year graduate-level course in transmission lines in electrical engineering and computer engineering curricula. …”

“…What You Will Learn Understand the concepts of ROS, the command-line tools, visualization GUIs, and how to debug ROS Connect robot sensors and actuators to ROS Obtain and analyze data from cameras and 3D sensors Dig deep into the ROS Pluginlib, ROS nodelets, and Gazebo plugins Interface I/O boards such as Arduino, robot sensors, and high-end actuators with ROS Get to grips with teleoperating robots using hand gestures Build ROS-based applications using Matlab and Android Build interactive applications using TurtleBot In Detail This learning path is designed to help you program and build your robots using open source ROS libraries and tools. …”

“…What you will learn Set up your Julia environment to achieve high productivity Create your own types to extend the built-in type system Visualize your data in Julia with plotting packages Explore the use of built-in macros for testing and debugging, among other uses Apply Julia to tackle problems concurrently Integrate Julia with other languages such as C, Python, and MATLAB Who this book is for Julia 1.0 Programming is for you if you are a statistician or data scientist who wants a crash course in the Julia programming language while building big data applications. …”

“…This Learning Path includes content from the following Packt products: Julia 1.0 Programming - Second Edition by Ivo Balbaert Julia Programming Projects by Adrian Salceanu What you will learn Create your own types to extend the built-in type system Visualize your data in Julia with plotting packages Explore the use of built-in macros for testing and debugging Integrate Julia with other languages such as C, Python, and MATLAB Analyze and manipulate datasets using Julia and DataFrames Develop and run a web app using Julia and the HTTP package Build a recommendation system using supervised machine learning Who this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. …”

“…What You Will Learn Control a robot without requiring a PhD in robotics Simulate and control a robot arm Control a flying robot Send your robot on an independent mission Learning how to control your own robots with external devices Program applications running on your robot Extend ROS itself Extend ROS with the MATLAB Robotics System Toolbox In Detail ROS is a robust robotics framework that works regardless of hardware architecture or hardware origin. …”

“…Complexity, delay, error control, and subjective quality in perceptual audio coding Computer exercises and MATLAB(R) hands-on projects complement the algorithm theory and reinforce concept learning. …”

“…Una extensión a la utilización de R para los cálculos numéricos y matemáticos para la ingeniería, con el mismo espíritu que MatLab y el uso básico de una herramienta de prototipado rápido de modelos de Machine Learning (BigML) en «point and click», también permitirán al lector que no quiera utilizar R producir modelos de predicción sin codificar. …”
Acceso con credenciales UPSA.