R2021b - Updates to the MATLAB and Simulink product families - MATLAB & Simulink

R2021b at a Glance

 

Discover What's New

Get more out of MATLAB and Simulink by downloading the latest release.

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    R2021b Release Highlights

    New Products

    Major Updates

    • Lidar Toolbox - Use Lidar Viewer app to visualize, analyze, and preprocess lidar point clouds interactively
    • Simulink Code Inspector - Use Code Inspector contextual tab to check compatibility, inspect code and view results directly in the model
    • Simulink Control Design - Design Model Reference Adaptive Controllers
    • Symbolic Math Toolbox - Get guidance for symbolic workflows with next-step suggestions in MATLAB Live Editor
    • Wavelet Toolbox - Use wavelet analysis to process and extract features for signals and images for AI workflows

    Release Details by Product

    MATLAB Product Family

    MATLAB

    • Editor: Explore new capabilities for code refactoring and block editing, as well as improved code suggestions, code completion, and debugger
    • Python Interface: Run Python commands and scripts from MATLAB
    • BackgroundPool: Run MATLAB functions on a background thread
    • Live Editor Tasks: Interactively summarize, transform, and filter groups of data (compute by group) and center and scale data (normalize data)
    • trenddecomp Function: Find trends in data
    • HDF5: Support for HDF5 version 1.10, including Single-Writer/Multiple-Reader (SWMR), Virtual Dataset (VDS), and Metadata Cache Fine-Tuning
    • Hardware: Use new apps for communicating with devices via serial (serial explorer) and TCP/IP (TCP/IP explorer)
    • ode78 and ode89 Functions: Use high-order Runge-Kutta solvers for ordinary differential equations
    • Projects: Organize, manage, and share your work using projects in MATLAB Online

    Lidar Toolbox

    • Lidar Viewer App: Visualize, analyze, and preprocess lidar point clouds interactively using the Lidar Viewer app
    • Aerial Lidar Processing: Apply deep learning and SLAM algorithms on aerial lidar data

    Wavelet Toolbox

    • Machine Learning and Deep Learning Feature Extraction: Perform signal and image analysis, preprocessing, and feature extraction with wavelet techniques and interactive apps for AI models
    • Acceleration and Deployment: Speed up wavelet algorithms using multicore processors and GPUs; generate code for desktop prototyping and embedded deployment

    Simulink Product Family

    Simulink

    • Multiple Simulations Panel: Run multiple simulations for different scenarios from Simulink Editor
    • Custom Tabs: Create custom Simulink toolstrip tabs
    • Mini Map: Determine context when viewing part of a block diagram

    Stateflow

    • Entry and Exit Junctions: Create entry and exit connections across hierarchy boundaries

    System Composer

    • Physical Interfaces with Simscape: Create physical interfaces, ports, and connections on components
    • Software Architectures: Create software architectures from existing components
    • Test Harness Support: Create test harnesses for System Composer components

    Simulink Compiler

    •  Runtime Parameter Tuning: Tune parameters while a deployed simulation is running

    AI, Data Science, and Statistics

    Statistics and Machine Learning Toolbox

    • Shallow Neural Networks: Use in Simulink as native blocks; automate hyperparameter tuning
    • Machine Learning: Explore k-means clustering in a live task and use isolation forest for anomaly detection
    • Deployment: Export models from the Classification and Regression Learner app to MATLAB Production Server

    Deep Learning Toolbox

    • 1D Convolutional Networks: Create and train networks for sequence and time-series data
    • Deep Network Designer: Export trained networks to Simulink
    • Neural ODEs: Compute deep learning solution of nonstiff ordinary differential equations using dlode45

    Control Systems

    Simulink Control Design

    • Model Reference Adaptive Control Block: Design and simulate Model Reference Adaptive Controllers

    Reinforcement Learning Toolbox

    • Rewards Generation: Automatically generate reward functions from controller specifications

    Model Predictive Control Toolbox

    • Nonlinear MPC: Implement multistage nonlinear MPC controllers with the Embotech FORCESPRO solver

    System Identification Toolbox

    • Nonlinear ARX Models: Create models that use regression functions based on machine learning algorithms

    Predictive Maintenance Toolbox

    • Diagnostic Feature Designer: Rank unlabeled features, and generate spectral features for characteristic fault frequency bands in rotating machinery

    RF and Mixed-Signal

    RF PCB Toolbox

    • New Product: Perform electromagnetic analysis of printed circuit boards

    Signal Integrity Toolbox

    • New Product: Simulate and analyze high-speed serial and parallel links

    Math and Optimization

    Symbolic Math Toolbox

    • Next-Step Suggestions: Get guidance for symbolic workflows with next-step suggestions in MATLAB Live Editor

    Global Optimization Toolbox

    • Problem-Based Workflow: Solve nonsmooth or global optimization problems using the problem-based optimization workflow