R2021b at a Glance

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