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MATLAB R2017b (9.3)

Matlab r2017 icon
NameMATLAB_R2017b
Size12.35 GB
Created on2017-12-28 10:21:59
Hash8bd1168b41d0a1e4d2b4bda2d4843a69fc4329c6
FilesMATLAB_R2017b (12.35 GB)

Descriptions for MATLAB R2017b (9.3)

Name: MATLAB
Version: 9.3 R2017b
Released: Sep 21st, 2017
Developer: The MathWorks Inc
Mac Platform: Intel
OS Version: OS X 10.10 or later
Processor type(s) & speed: 64-bit processor

Includes: K

Web Site: http://www.mathworks.com/products/matlab/

Overview

Integrates mathematical computing, visualization and a language to provide a flexible environment for technical computing, visualization and programming

MATLAB is an advanced interactive environment specially designed to greatly boost your productivity while performing numerical computation, programming and visualization tasks on a Mac.

Multi-paradigm numerical computing environment

With the help of MATLAB, you can analyze data, create applications, models and develop algorithms and, furthermore, thanks to its large selection of inbuilt tools, as well as language and built-in mathematical algorithms you can scrutinize various approaches and find a solution much faster than with traditional programming languages and spreadsheets.

MATLAB can be used for a wide variety of applications that range from communications and signal processing to control systems, video processing, computational finance and biology, test and measurement.

Numeric computation

You can use MATLAB’s built-in mathematical tools to solve all sorts of engineering and science problems. The provided numerical computation methods can help you develop algorithms, analyze data or create models.

The MATLAB language cover numerous mathematical functions with support for popular science and engineering operations. Vector and matrix calculations are smoothly executed thanks to the processor-optimized libraries used by the core math functions.

Data analyzer and visualizer

Furthermore, MATLAB comes with the necessary tools to collect, analyze and visualize data in order to gain a better understanding of your data. You can also document and share the obtained results using complex plots and reports.

What is more, you can acquire data from files, databases, external devices or other applications. MATLAB features support for spreadsheet files, text and binary files, multimedia files, as well as netCDF and HDF files.

Once the data is collected, you can manage, filter and pre-process it, perform exploratory data analysis and reveal trends, test assumptions and construct descriptive models. On top of that, you can also use the built-in 2D and 3D plot functions along with the volume visualization functions to display your data.

Flexible MATLAB language

The MATLAB language offers native support for matrix and vector operations that you can use to solve a plethora of problems from different fields.

Moreover, you can write programs and create algorithms without performing low-level administrative tasks. In your development process you can take advantage of numerous development tools, deploy applications and even generate standalone C code.

What’s new in MATLAB 9.3 R2017b

Desktop:
  • Live Editor: Write MATLAB commands with automated, contextual hints for arguments, property values, and alternative syntaxes
  • Live Editor: Export live scripts to LaTeX format
  • Live Editor: Display high-resolution plots in PDF output
  • Live Editor: Horizontally align text, equations, and images
  • Live Editor: Automatically match delimiters and wrap comments while editing code
  • Live Editor: View and scroll through table data, including variable and row names
  • Live Editor: Check code for errors and warnings using the message bar and message indicator
  • Documentation: Use the Live Editor in a web browser to open, edit, and run MATLAB online documentation examples
  • MATLAB Drive: Store, access, and manage your files from anywhere
  • Add-On Manager: Customize your MATLAB environment by enabling and disabling add-ons
  • Add-On Manager: Find installed add-ons faster using sort and search
  • Toolbox Packaging: Create a Getting Started Guide for your toolbox from a Live Script template
  • Toolbox Packaging: Share your toolbox on File Exchange directly when you package it
  • Command Window: View updated display for cell arrays
  • Language and Programming
  • Code Compatibility Report: Generate a report that helps the updating of code to a newer MATLAB release
  • isStringScalar Function: Determine whether input is a string array with one element
  • convertStringsToChars and convertCharsToStrings Functions: Enable your code to accept all text types as inputs without otherwise altering your code
  • arrayfun, cellfun, and structfun Functions: Return object arrays as output arguments
  • Scripts: Run sections in scripts containing local functions
  • isfile and isfolder Functions: Determine if input is a file or a folder
  • Functionality being removed or changed
Mathematics:
  • decomposition Object: Solve linear systems repeatedly with improved performance
  • lsqminnorm Function: Find minimum-norm solution of underdetermined linear system
  • dissect Function: Reorder sparse matrix columns using nested dissection ordering
  • vecnorm Function: Compute vector-wise norms of arrays
  • polyshape Object: Create, analyze, and visualize 2-D polygons
  • eigs Function: Improved algorithm and new options
  • svds Function: Set options with name-value pairs
  • Interpolation Functions: Method for modified Akima cubic Hermite interpolation
  • convn Function: Compute convolutions on multidimensional arrays with improved performance
  • subgraph and highlight Functions: Specify graph nodes with logical vector
  • Functionality being removed or changed
Graphics:
  • geobubble Function: Create an interactive map with bubbles whose size and color vary with data values
  • wordcloud Function: Display words at different sizes based on frequency or custom size data
  • binscatter Function: Visualize data density with dynamic bin size adjustment
  • Tall Array Support: Visualize out-of-memory data using plot, scatter, and binscatter
  • heatmap Function: Sort rows and columns and use custom labels in a heatmap
  • bar Function: Control individual bar colors
  • Chart Colors: Create bar and area charts with new default colors
  • Axes Object: Specify the target axes for more functions
  • Functionality being removed or changed
  • Data Import and Export
  • Custom Datastore: Build a customized datastore
  • datastore Function: Work with data stored in Windows Azure Blob Storage
  • datastore Function: Access Hadoop HDFS data more easily
  • FileDatastore Object: Create uniform output from datastore
  • HDF5 Functions: Create datasets, groups, attributes, links, and named datatypes using non-ASCII characters
  • Web services: Skip server name verification in certificates
  • jsonencode Function: Encode NaN and Inf as null
  • Functionality being removed or changed
Data Analysis:
  • ischange Function: Detect abrupt changes in data
  • islocalmin and islocalmax Functions: Detect local minima and maxima in data
  • rescale Function: Scale data to a specified range
  • tall Arrays: Operate on tall arrays with more functions, including fillmissing, filter, median, polyfit, and synchronize
  • tall Array Indexing: Use subscripted assignment with tall arrays
  • tallrng Function: Control random number generator used by tall arrays
  • timetable Data Container: Specify whether each variable in a timetable contains continuous or discrete data using the VariableContinuity property
  • mink and maxk Functions: Find the k smallest or largest elements in an array
  • topkrows Function: Find the k top rows in sorted order for numeric arrays, tables, and timetables
App Building:
  • App Designer: Create apps with a wide variety of 2-D and 3-D plots
  • App Designer: Add menus to an app from the Component Library
  • App Designer: Specify input arguments when running an app
  • App Designer: Add a summary, description, and screenshot for app packaging and compiling
  • App Designer: Improved component Properties pane in Code View
  • App Designer: Edit tick labels for gauges, knobs, and sliders directly in the canvas
  • uitree and uitreenode Functions: Create trees and tree nodes in apps
  • uiconfirm Function: Create modal in-app confirmation dialog boxes
  • Toolbox Packaging: Add App Designer apps to the Apps Gallery upon toolbox installation
  • MATLAB Online: Run App Designer apps in MATLAB Online
Performance:
  • App Designer: Load apps faster
  • Execution Engine: Improved performance for vectorized math on CPUs with AVX2
  • Live Editor: Run live scripts with loops faster
Hardware Support:
  • Arduino: Wirelessly connect to Arduino boards using low-cost Bluetooth adaptors
  • Arduino Setup UI: Set up a connection to your Arduino board over USB, Bluetooth, or WiFi
  • Arduino Plug-In Detection: Discover available Arduino support and examples when plugging a compatible Arduino board
  • iPhone and Android Sensors: Log sensor data locally on Android or iOS devices for later analysis
Advanced Software Development:
  • MATLAB Engine API for C++: Run MATLAB code from C++ programs with object-oriented programming support and asynchronous execution
  • MATLAB Engine API for C++: Pass data between C++ programs and MATLAB using MATLAB Data Array
  • Java SE 8: MATLAB support, providing improved security and access to new Java features
  • MinGW 5.3: MATLAB support
  • Microsoft Visual Studio 2017: MATLAB support for Microsoft Visual Studio 2017 Community, Professional, and Enterprise editions
  • Compiler support changed for building MEX files and standalone MATLAB engine and MAT-file applications
  • Python Version 3.6: MATLAB support
  • Perl 5.24.1: MATLAB support
  • MATLAB Handle class method: Add a listener for an event without binding the listener to the source object
  • Unit Testing Framework: Provide code coverage reports in the Cobertura format for improved continuous integration workflows
  • Unit Testing Framework: Generate HTML report of a test run
  • Unit Testing Framework: Write tests as live scripts
  • Unit Testing Framework: Specify additional diagnostics to evaluate upon failures using the onFailure method
  • Performance Testing Framework: Define multiple measurement boundaries in test methods
  • Mocking Framework: Construct mocks for classes that have Abstract methods with other attributes
  • Source Control Integration: Show differences from parent files and save copies in Git Branches
  • Functionality being removed or changed

Screenshots

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