Ключевые возможности:

Ядро MATLAB позволяет максимально просто работать с матрицами реальных, комплексных и аналитических типов данных. Содержит встроенные функции линейной алгебры (LAPACK, BLAS), быстрого Фурье преобразования (FFTW), функции для работы с полиномами, функции базовой статистики и численного решения дифференциальных уравнений. Все встроенные функции ядра MATLAB разработаны и оптимизированы специалистами и работают быстрее или так же, как их эквивалент на C/C++
• Платформонезависимый, высокоуровневый язык программирования, ориентированный на матричные вычисления и разработку алгоритмов
• Интерактивная среда для разработки кода, управления файлами и данными
• Функции линейной алгебры, статистики, анализ Фурье, решение дифференциальных уравнений и др.
• Богатые средства визуализации, 2-D и 3-D графика
• Встроенные средства разработки пользовательского интерфейса для создания законченных приложений на MATLAB
• Средства интеграции с C/C++, наследование кода, ActiveX технологии
• Доступ к функциям .NET

Что нового:

Desktop
Add-On Explorer: Add capabilities to MATLAB, including community-authored and MathWorks toolboxes, apps, functions, models, and hardware support
Documentation: Find information faster with redesigned Help navigation and browser-style keyboard shortcuts
Tab Completion: Complete commands with corrected capitalization
Command Suggestions: Get suggested corrections for mistyped function names when calling help command
Language and Programming
findgroups and splitapply Functions: Split data into groups and apply functions to each group of data
NaT Function: Create array of Not-a-Time values
timezones Function: Display list of time zone names
help Command: Specify a variable as input to the help command instead of specifying the variable class name
Advanced Software Development
MATLAB Interface to Python: Clear Python class definitions with clear classes command, useful when reloading revised Python classes
MATLAB Interface to Python: Pass a handle to a Python function to other Python functions called from MATLAB
MATLAB Engine for Python: Call MATLAB functions and objects from Python by connecting to a running session of MATLAB
MEX Compiler Support: Compile MEX files with freely available MinGW-w64 compiler on 64-bit Windows
Unit Testing Framework: Improve continuous integration workflows with diagnostics from the TAP plugin and a JUnit-style XML plugin
Unit Testing Framework: Customize the test runner with plugins that immediately report finalized results and perform system-wide qualifications
Unit Testing Framework: Run tests in parallel when available using the runtests function with the UseParallel option
Unit Testing Framework: Detect and prevent warnings issued by tests using the new FailOnWarningsPlugin
Mathematics
graph and digraph Classes: Create, analyze, and visualize graphs and networks
histcounts2 Function: Bin bivariate data
deg2rad and rad2deg Functions: Convert between radians and degrees
datetime Arrays: Interpolate dates and times using interp1 function
duration Arrays: Perform computations on durations using interp1, eps, cummax, cummin, cumsum, mod, and rem functions
Data Import and Export
Excel Spreadsheets: Read and write to the same spreadsheet repeatedly with improved performance of xlsread, xlswrite, readtable, and writetable functions
datastore Function: Import data from image collections that are too large to fit in memory as an ImageDatastore
datastore Function: Import data from text files with support for additional character encoding schemes with TabularTextDatastore
VideoReader Object: Read streams of data more quickly from video files on Mac
Graphics
Graphics Display: Leverage DPI-aware MATLAB graphics for Apple Retina displays and high-resolution displays on Windows
Axes Object: Set the location of each axis in a plot to cross at the origin
Numeric Ruler Object: Customize tick format, exponent, and text style to control the appearance of an individual axis in a plot
histogram2 Function: Plot bivariate histograms with control over bins, normalization, and display
MATLAB Charts: Use transparency in bar, scatter, and area charts
GUI Building
UI Display: Create DPI-aware UIs for Apple Retina displays and high-resolution displays on Windows
Performance
MATLAB Execution Engine: Run programs faster with redesigned architecture
table Data Type: Access data with improved performance when using dot-parentheses
Categorical Arrays: Create a larger number of categories, with improved memory efficiency and performance
Hardware Support
Raspberry Pi 2 Model B: Acquire sensor and image data from Raspberry Pi 2 boards using the MATLAB Support Package for Raspberry Pi Hardware
BeagleBone Black: Acquire sensor and image data from BeagleBone Black boards using the MATLAB Support Package for BeagleBone Black Hardware
iOS Sensors: Acquire sensor data from Apple iOS mobile devices using the
MATLAB Support Package for Apple iOS Sensors