MATLAB eBooks
Practical MATLAB Deep Learning, 2nd Edition
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning. Over the course of the book, you'll learn to model complex systems and apply deep learning to problems in those areas. Applications include: Aircraft navigation; An aircraft that lands on Titan, the moon of Saturn, using reinforcement learning; Stock market prediction; Natural language processing; Music creation usng generative deep learning; Plasma control; Earth sensor processing for spacecraft; MATLAB Bluetooth data acquisition applied to dance physics. ...
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning. Over the course of the book, you'll learn to model complex systems and apply deep learning to problems in those areas. Applications include: Aircraft navigation; An aircraft that lands on Titan, the moon of Saturn, using reinforcement learning; Stock market prediction; Natural language processing; Music creation usng generative deep learning; Plasma control; Earth sensor processing for spacecraft; MATLAB Bluetooth data acquisition applied to dance physics. ...
Python for MATLAB Development
Python for MATLAB Development shows you how to enhance MATLAB with Python solutions to a vast array of computational problems in science, engineering, artificial intelligence, statistics, finance, and simulation. It is three books in one: A thorough Python tutorial that leverages your existing MATLAB knowledge with a comprehensive collection of MATLAB/Python equivalent expressions; A reference guide to setting up and managing a Python environment that integrates cleanly with MATLAB; A collection of recipes that demonstrate Python solutions invoked directly from MATLAB . The demonstrated techniques and explanations will help you solve your own challenging problems in MATLAB using open source Python modules. Python is the ultimate MATLAB Toolbox and this book is your guide to its use. ...
Python for MATLAB Development shows you how to enhance MATLAB with Python solutions to a vast array of computational problems in science, engineering, artificial intelligence, statistics, finance, and simulation. It is three books in one: A thorough Python tutorial that leverages your existing MATLAB knowledge with a comprehensive collection of MATLAB/Python equivalent expressions; A reference guide to setting up and managing a Python environment that integrates cleanly with MATLAB; A collection of recipes that demonstrate Python solutions invoked directly from MATLAB . The demonstrated techniques and explanations will help you solve your own challenging problems in MATLAB using open source Python modules. Python is the ultimate MATLAB Toolbox and this book is your guide to its use. ...
Cryptography and Cryptanalysis in MATLAB
Master the essentials of cryptography and cryptanalysis and learn how to put them to practical use. Each chapter of this book starts with an introduction to the concepts on which cryptographic algorithms are based and how they are used in practice, providing fully working examples for each of the algorithms presented. Implementation sections will guide you through the entire process of writing your own applications and programs using MATLAB. Cryptography and Cryptanalysis in MATLAB will serve as your definitive go-to cryptography reference, whether you are a student, professional developer, or researcher, showing how a multitude of cryptographic challenges can be overcome using the powerful tools of MATLAB. ...
Master the essentials of cryptography and cryptanalysis and learn how to put them to practical use. Each chapter of this book starts with an introduction to the concepts on which cryptographic algorithms are based and how they are used in practice, providing fully working examples for each of the algorithms presented. Implementation sections will guide you through the entire process of writing your own applications and programs using MATLAB. Cryptography and Cryptanalysis in MATLAB will serve as your definitive go-to cryptography reference, whether you are a student, professional developer, or researcher, showing how a multitude of cryptographic challenges can be overcome using the powerful tools of MATLAB. ...
MATLAB Recipes, 2nd Edition
Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition prov ...
Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition prov ...
Practical MATLAB Modeling with Simulink
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. 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. 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. Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling. 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. ...
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. 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. 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. Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling. 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. ...
Practical MATLAB Deep Learning
Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You'll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images. Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. Explore deep learning using MATLAB and compare it to algorithms; Write a deep learning function in MATLAB and train it with examples; Use MATLAB toolboxes related to deep learning; Implement tokamak disruption prediction. ...
Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You'll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images. Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. Explore deep learning using MATLAB and compare it to algorithms; Write a deep learning function in MATLAB and train it with examples; Use MATLAB toolboxes related to deep learning; Implement tokamak disruption prediction. ...
Physical Modeling in MATLAB, 3rd Edition
Modeling and simulation are powerful tools for explaining the world, making predictions, designing things that work, and making them work better. Learning to use these tools can be difficult; this book is my attempt to make the experience as enjoyable and productive as possible. Modeling and simulation are powerful tools for explaining the world, making predictions, designing things that work, and making them work better. Learning to use these tools can be difficult; this book is my attempt to make the experience as enjoyable and productive as possible. By reading this book - and working on the exercises - you will learn some programming, some modeling, and some simulation: With basic programming skills, you can create models for a wide range of physical systems. My goal is to help you develop these skills in a way you can apply immediately to real-world problems; This book presents the entire modeling process, including model selection, analysis, simulation, and validation. I ex ...
Modeling and simulation are powerful tools for explaining the world, making predictions, designing things that work, and making them work better. Learning to use these tools can be difficult; this book is my attempt to make the experience as enjoyable and productive as possible. Modeling and simulation are powerful tools for explaining the world, making predictions, designing things that work, and making them work better. Learning to use these tools can be difficult; this book is my attempt to make the experience as enjoyable and productive as possible. By reading this book - and working on the exercises - you will learn some programming, some modeling, and some simulation: With basic programming skills, you can create models for a wide range of physical systems. My goal is to help you develop these skills in a way you can apply immediately to real-world problems; This book presents the entire modeling process, including model selection, analysis, simulation, and validation. I ex ...
MATLAB Machine Learning Recipes, 2nd Edition
Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. How to write code for machine learning, adaptive control and estimation using MATLAB; How these three areas complement each other; How these three areas are needed for robust machine learning applications; How to use MATLAB graphics and visualization tools for machine learning; How to code real world examples in MATLAB ...
Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. How to write code for machine learning, adaptive control and estimation using MATLAB; How these three areas complement each other; How these three areas are needed for robust machine learning applications; How to use MATLAB graphics and visualization tools for machine learning; How to code real world examples in MATLAB ...
MATLAB Notes for Professionals
The MATLAB Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. ...
The MATLAB Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. ...
Block Trace Analysis and Storage System Optimization
Understand the fundamental factors of data storage system performance and master an essential analytical skill using block trace via applications such as MATLAB and Python tools. You will increase your productivity and learn the best techniques for doing specific tasks (such as analyzing the IO pattern in a quantitative way, identifying the storage system bottleneck, and designing the cache policy). In the new era of IoT, big data, and cloud systems, better performance and higher density of storage systems has become crucial. To increase data storage density, new techniques have evolved and hybrid and parallel access techniques - together with specially designed IO scheduling and data migration algorithms - are being deployed to develop high-performance data storage solutions. Among the various storage system performance analysis techniques, IO event trace analysis (block-level trace analysis particularly) is one of the most common approaches for system optimization and desig ...
Understand the fundamental factors of data storage system performance and master an essential analytical skill using block trace via applications such as MATLAB and Python tools. You will increase your productivity and learn the best techniques for doing specific tasks (such as analyzing the IO pattern in a quantitative way, identifying the storage system bottleneck, and designing the cache policy). In the new era of IoT, big data, and cloud systems, better performance and higher density of storage systems has become crucial. To increase data storage density, new techniques have evolved and hybrid and parallel access techniques - together with specially designed IO scheduling and data migration algorithms - are being deployed to develop high-performance data storage solutions. Among the various storage system performance analysis techniques, IO event trace analysis (block-level trace analysis particularly) is one of the most common approaches for system optimization and desig ...
Programming for Computations - MATLAB/Octave
This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification. ...
This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification. ...