R2026a Release Highlights

R2026a

New Products

• Simulink Copilot – AI assistant optimized for Simulink.
• MATLAB Course Designer – Create courses, courseware, labs, and assessments using MATLAB and Simulink.
• Polyspace as You Code – Identify coding standard violations and software vulnerabilities from your IDE.
• Polyspace Copilot – AI assistant optimized for Polyspace.
• Raspberry Pi Blockset – Design, simulate, and deploy applications for Raspberry Pi.
• Simulink FMU Builder – Create standalone FMUs from Simulink models and C/C++ code.
• STM32 Microcontroller Blockset – Design, simulate, and implement applications for STMicroelectronics STM32 microcontrollers.
• Wireless Network Toolbox – Model, simulate, analyze, and visualize wireless communication networks.

Major Updates

• Econometrics Toolbox – Apply enhancements from the Econometric Modeler app for filtering, simulation, forecasting, and visualization; leverage advanced panel data regression and Bayesian modeling for comprehensive analysis.
• Mapping Toolbox – Enhance geospatial capabilities with 3D building visualization, image overlays, and raster maps.
• MATLAB Test – Generate starter tests, equivalence tests, and tests from your command history; generate tests using MATLAB Copilot; save time by running only the tests related to your current file.
• Polyspace Bug Finder – Configure and review Polyspace projects faster with the new desktop app, shared with Polyspace Test; extend coding rules checking with custom checkers and full MISRA™ C/C++ 2023 support.
• Polyspace Test – Integrate Bug Finder, Code Prover, and Requirements Toolbox with Polyspace Test; use Python^® API for test creation and execution; generate AUTOSAR-aware stubs for testing of functions.
• RF PCB Toolbox – Analyze complex PCBs: import ODB++ databases, perform finite element and DC electromagnetic analysis, and integrate components in RF Blockset for wireless system simulation.
• RF Toolbox – Use the Idealized Baseband Library to model RF components (amplifiers, filters, S-parameters, and mixers) in MATLAB and simulate end-to-end wireless communications and radar systems.
• Signal Processing Toolbox – Design and analyze digital filters with the new Filter Designer and Filter Analyzer apps; label time-frequency maps with Signal Labeler; extract features interactively with Signal Feature Extractor.
• Simulink Real-Time – Perform HIL tests on Speedgoat hardware running the new Linux based RTOS; apply enhanced instrumentation, including dynamic data logging and improved external APIs.

Release Resources

• Release Notes
• License-Related Changes
• Software Maintenance Service
• System Requirements
• Previous Releases

Release Highlights

[MATLAB] Web Canvas Create webpages with interactive graphics that do not require MATLAB.		[Simulink] Rich Context Menus   Access actions from a simplified context menu that prioritizes frequently used functionality.
MATLAB Java Runtime – Install your own version of compatible OpenJDK releases. Python Integration – Use the External Languages panel to view, create, and manage Python environments in MATLAB; automatically convert MATLAB string arrays to a Python list or NumPy string array. Sharing from MATLAB Drive – Share files and apps stored in MATLAB Drive directly from the MATLAB Desktop and App Designer, respectively. JSON Files – Read and write JSON data as tables and timetables. Live Editor – Create multilevel lists; run user-defined code by clicking a button control in your live script. raincloudplot Function – Visualize grouped numeric data by using rain cloud plots.		Simulink Compare and Merge Data Dictionaries – Compare Simulink Data Dictionaries (SLDD) to identify differences in design data, configuration sets, and more; merge desired changes into a new target SLDD file. Model Reference Rebuild – Customize the default rebuild behavior for new models to avoid unnecessary compilations. Enhanced Language Support for C Function Block – Simulate C or C++ code using the C Function block without language limitations or the need for additional wrappers. Componentization Online Training Course – Learn the core principles of component-based modeling in Simulink, focusing on organizing, reusing, and protecting model components for scalable system design.