MathWorks MATLAB R2017a (9.2.0.538062) macOS
MathWorks MATLAB R2017a (9.2.0.538062) macOS | 9.92 GB
Millions of engineers and scientists worldwide use MATLAB to analyze and design the systems and products transforming our world. MATLAB is in automobile active safety systems, interplanetary spacecraft, health monitoring devices, smart power grids, and LTE cellular networks. It is used for machine learning, signal processing, image processing, computer vision, communications, computational finance, control design, robotics, and much more.
Math. Graphics. Programming.
The MATLAB platform is optimized for solving engineering and scientific problems. The matrix-based MATLAB language is the world’s most natural way to express computational mathematics. Built-in graphics make it easy to visualize and gain insights from data. A vast library of prebuilt toolboxes lets you get started right away with algorithms essential to your domain. The desktop environment invites experimentation, exploration, and discovery. These MATLAB tools and capabilities are all rigorously tested and designed to work together.
Scale. Integrate. Deploy.
MATLAB helps you take your ideas beyond the desktop. You can run your analyses on larger data sets and scale up to clusters and clouds. MATLAB code can be integrated with other languages, enabling you to deploy algorithms and applications within web, enterprise, and production systems.
Key Features
- High-level language for scientific and engineering computing
- Desktop environment tuned for iterative exploration, design, and problem-solving
- Graphics for visualizing data and tools for creating custom plots
- Apps for curve fitting, data classification, signal analysis, and many other domain-specific tasks
- Add-on toolboxes for a wide range of engineering and scientific applications
- Tools for building applications with custom user interfaces
- Interfaces to C/C++, Java®, .NET, Python®, SQL, Hadoop®, and Microsoft® Excel®
- Royalty-free deployment options for sharing MATLAB programs with end users
Why MATLAB?
MATLAB is the easiest and most productive software for engineers and scientists. Whether you’re analyzing data, developing algorithms, or creating models, MATLAB provides an environment that invites exploration and discovery. It combines a high-level language with a desktop environment tuned for iterative engineering and scientific workflows.
MATLAB Speaks Math
The matrix-based MATLAB language is the world’s most natural way to express computational mathematics. MATLAB supports both numeric and symbolic calculations. Linear algebra in MATLAB looks like linear algebra in a textbook; symbolic calculations look like the equations you write on paper. This makes it straightforward to capture the mathematics behind your ideas, which means your code is easier to write, easier to read and understand, and easier to maintain.
You can trust the results of your computations. MATLAB, which has strong roots in the numerical analysis research community, is known for its impeccable numerics. A MathWorks team of 350 engineers continuously verifies quality by running millions of tests on the MATLAB code base every day.
MATLAB does the hard work to ensure your code runs quickly. Math operations are distributed across multiple cores on your computer, library calls are heavily optimized, and all code is just-in-time compiled. You can run your algorithms in parallel by changing for-loops into parallel for-loops or by changing standard arrays into GPU or distributed arrays. Run parallel algorithms in infinitely scalable public or private clouds with no code changes.
The MATLAB language also provides features of traditional programming languages, including flow control, error handling, object-oriented programming, unit testing, and source control integration.
MATLAB Is Designed for Engineers and Scientists
MATLAB provides a desktop environment tuned for iterative engineering and scientific workflows. Integrated tools support simultaneous exploration of data and programs, letting you evaluate more ideas in less time.
- You can interactively preview, select, and preprocess the data you want to import.
- An extensive set of built-in math functions supports your engineering and scientific analysis.
- 2D and 3D plotting functions enable you to visualize and understand your data and communicate results.
- MATLAB apps allow you to perform common engineering tasks without having to program. Visualize how different algorithms work with your data, and iterate until you’ve got the results you want.
- The integrated editing and debugging tools let you quickly explore multiple options, refine your analysis, and iterate to an optimal solution.
- You can capture your work as sharable, interactive narratives.
Comprehensive, professional documentation written by engineers and scientists is always at your fingertips to keep you productive. Reliable, real-time technical support staff answers your questions quickly. And you can tap into the knowledge and experience of over 100,000 community members and MathWorks engineers on MATLAB Central, an open exchange for MATLAB and Simulink® users.
MATLAB and add-on toolboxes are integrated with each other and designed to work together. They offer professionally developed, rigorously tested, field-hardened, and fully documented functionality specifically for scientific and engineering applications
MATLAB Integrates Workflows
Major engineering and scientific challenges require broad coordination to take ideas to implementation. Every handoff along the way adds errors and delays.
MATLAB automates the entire path from research through production. You can:
- Build and package custom MATLAB apps and toolboxes to share with other MATLAB users.
- Create standalone executables to share with others who do not have MATLAB.
- Integrate with C/C++, Java, .NET, and Python. Call those languages directly from MATLAB, or package MATLAB algorithms and applications for deployment within web, enterprise, and production systems.
- Convert MATLAB algorithms to C, HDL, and PLC code to run on embedded devices.
- Deploy MATLAB code to run on production Hadoop systems.
MATLAB is also a key part of Model-Based Design, which is used for multidomain simulation, physical and discrete-event simulation, and verification and code generation.
Desktop
- Live Editor: Edit a figure interactively including title, labels, legend, and other annotations
- Live Editor: Get suggestions for mistyped commands and variables
- Live Editor: Copy live script outputs to other applications
- Live Editor: Hover over variables to see their current value
- Add-On Explorer: Discover and install File Exchange submissions hosted on GitHub in Add-On Explorer
- MATLAB Online: Access MATLAB through your web browser
Language and Programming
- string Arrays: Create string arrays using double quotes
- missing Function: Assign missing values in core data types, including double, datetime, and string arrays
- issortedrows Function: Determine if matrix and table rows are sorted
- sort and sortrows Functions: Specify options for sorting complex numbers and placing missing elements
- issorted Function: Query sort order with monotonic, strictly monotonic, strictly ascending, and strictly descending options
Graphics
- heatmap Function: Visualize table or matrix data as a heatmap
- legend Function: Create legends that update when data is added to or removed from the axes
- Categorical Plotting: Use categorical data in common plotting functions and customize axes with categorical rulers
- histogram Function: Plot histograms of datetime and duration data
Data Import and Export
- datastore and tabularTextDatastore Functions: Automatically detect and return date and time data in text files
- Import Tool: Import strings and categorical arrays interactively
- detectImportOptions Function: Control import properties of fixed-width text files
- RESTful web services: Support for PUT and DELETE HTTP methods in webread, webwrite, and websave
Data Analysis
- tall Arrays: Operate on tall arrays with more functions, including ismember, sort, conv, and moving statistics functions
- isoutlier and filloutliers Functions: Detect and replace outliers in an array or table
- smoothdata Function: Smooth noisy data in an array or table with filtering or local regression
- summary Function: Calculate summary statistics and variable information in tables and timetables
- movmad and movprod Functions: Compute moving median absolute deviation and moving product of an array
- bounds Function: Simultaneously determine the smallest and largest elements of an array
- fillmissing Function: Replace missing data in an array or table using moving mean or moving median option
App Building
- App Designer: Learn to build apps using an interactive tutorial
- App Designer: Zoom and pan plots
- App Designer: Configure columns of a table to automatically fill the entire width of the table
- App Designer: Manage common design-time settings using the Preferences dialog box
Performance
- Execution Engine: Improved performance for setting MATLAB object properties
- save Function: Save MAT v7.3 files without compression for improved performance on some storage devices
- memoize Function: Cache results of a function to avoid rerunning when called with the same inputs
- Scripts: Improved performance of scripts with lower script overhead
- try, catch Block: Improved performance of try blocks with lower execution overhead
Hardware Support
- Arduino: Read from quadrature encoders
- Arduino: Wirelessly connect to Arduino MKR1000 board over WiFi
- iPhone and Android Sensors: Log sensor data locally on Android or iOS devices for later analysis
Advanced Software Development
- Object Properties: Validate object property values by their type, size, shape, or other parameters
- Mocking Framework: Isolate a portion of a system to test by imitating behavior of dependent components
- Unit Testing Framework: Capture screenshots and figures generated during tests using TestReportPlugin
- Unit Testing Framework: Control runtests function with debug, strict, and verbosity options
- Performance Testing Framework: View statistics from test measurements with the sampleSummary method