MathWorks MATLAB and Simulink Software Solutions
MATLAB for Smart Agriculture and Digital Farming
Agriculture
Drive development across digital agriculture, smart machinery, and sustainability.
MATLAB and Simulink are used by agritech companies to develop and test technologies across the agricultural value chain. These products support applications such as intelligent machinery, digital farming, and renewable energy systems, helping teams streamline development and explore sustainable solutions
Develop Smart Agricultural Machinery
Design and test control systems, perception algorithms, and autonomous capabilities for tractors, harvesters, and sprayers. Autonomous navigation and obstacle avoidance with sensor fusion and real-time data processing with Predictive maintenance and diagnostics.
Implement and Leverage Digital Agriculture
Leverage data analytics, AI based model to optimize farming operations such as Crop yield prediction using imagery from satellite and drone data, Machine learning for disease detection and classification, integration for real-time monitoring of field conditions and decision support systems for precision agriculture.
Optimize Energy Use in Agricultural Systems
Design and optimize renewable energy systems for agricultural use in Solar-powered irrigation, Wind and biomass energy modelling, energy storage and grid integration, hybrid system simulation and control.
MATLAB for Quantitative Finance and Risk Management
Quantitative Finance and Risk Management
Import data, develop algorithms, debug code, scale up processing power, and more.
Leading financial institutions use MATLAB to determine interest rates, perform stress tests, manage multi-billion dollar portfolios, and trade complex instruments in less than a second. They use MATLAB as an interface for importing historical and real-time market data from free and paid sources including Bloomberg, Refinitiv, and FRED
Investment Management
Build and evolve dashboards for portfolio managers, with intraday risk reporting, valuation, and trade execution capabilities. Optimize portfolios using prebuilt tools for mean-variance, conditional value-at-risk (CVaR), custom objectives, and Black-Litterman methods. Measure investment performance using risk-adjusted alphas, tracking errors, maximum drawdowns, and the Sharpe ratio.
Risk Management
Use statistical tests to assess model performance and generate regulatory reports. Analyze and backtest Value-at-Risk (VaR) and Expected Shortfall (ES) using expanded analytics and support for a broad range of risk factors. Perform scenario analysis and stress testing to assess portfolio sensitivity and resilience under adverse conditions. Streamline model risk management with validation tools and automated reporting. Accelerate large scale risk simulations with parallel computing capabilities. Build risk management systems or stress testing infrastructure for CCAR, DFAST, Basel III, and Solvency II.
Algorithmic Trading
Develop and backtest trading strategies using traditional methods (e.g., technical indicators or econometric models) or more cutting-edge machine learning algorithms. Execute trading strategies in real time using MATLAB code.
Financial Forecasting and Modelling
Use point-and click apps to fit time-series data with econometric models (e.g., ARMA, ARIMA, GARCH, EGARCH, GJR) or machine learning algorithms. Interface to DSGE models to forecast key economic variables. Use functions for interest rate modelling and forecasting based on parameters estimated from the Nelson-Siegel or Svensson models.
Derivatives Pricing
Calculate price and Greek variables of exotic options using Monte Carlo simulation in MATLAB for various pricing methods (e.g., closed-form equations, binomial trees, trinomial trees, and the stochastic volatility model) to price options. These include European options, American options, Asian options, barrier options, caps, floors, swaps, and multi-underlying asset derivatives. Run compute-intensive applications in parallel or deploy them to a GPU or Interface with Numerix.
Insurance and Actuarial Science
Analyze large data sets, create custom actuarial models, and easily accelerate the simulations using parallelization. Build custom risk models using MATLAB as a platform for Solvency II. Price various insurance products such as variable annuities, guaranteed minimum benefit options, term assurance, and endowment policies.
MATLAB for Medical Device Design and Testing
Design, simulate, and test next-generation medical devices while ensuring regulatory compliance.
MATLAB and Simulink are used to design, develop, and test medical imaging algorithms and devices while complying with industry regulations and standards such as IEC 62304 in the development process. Use computational modelling and simulation to train, validate, and integrate artificial intelligence (AI) models into the system design. Perform rapid prototyping with real-time hardware platforms.
Therapeutic Devices
MATLAB and Simulink enable engineers, researchers, and scientists to design, simulate, and test therapeutic devices while complying with industry regulations and standards. You can validate MATLAB and Simulink products for FDA/CE regulations and conform to standards such as IEC 62304 in the development process.
Medical Imaging
MATLAB and Simulink let you design, develop Prototype and implement high-performance image formation and reconstruction techniques. Create image processing algorithms for computer vision, radiomics, and computer-aided diagnosis. Train and validate explainable artificial intelligence (AI) and deep learning models. Deploy and share medical imaging applications in the cloud. Design and simulate antennas, arrays, power systems, and control systems for medical imaging devices.
Patient Monitoring
With MATLAB and Simulink, one can design, develop, simulate, and deploy patient monitoring devices and Software as a Medical Device (SaMD) applications in the cloud at scale while complying with global regulatory standards for medical devices such as IEC 62304.
Hearing Aids
MATLAB and Simulink enable engineers, researchers, and scientists to design, prototype, and test hearing aids and cochlear implants while complying with industry regulations and standards and integrate artificial intelligence (AI) models into hearing aids design. Simulate mixed-signal systems in the presence of noise, clock jitter, and other impairments. Design and test low-latency, low-energy wireless communication systems.
Surgical Devices
MATLAB® and Simulink® enable engineers, researchers, and scientists to design, prototype, and test surgical devices and robots while complying with industry regulations and standards such as IEC 62304 in the development process. Design and simulate algorithms for sensor data and control systems. Create embedded computer vision algorithms for real-time image processing Train, validate, and integrate artificial intelligence (AI) models into the system design and rapid prototyping with real-time hardware platforms.
In Vitro Diagnostic Devices
MATLAB and Simulink can be used to design and simulate algorithms for sensor data and control systems. Simulate and analyse life science data, including multi-omics, microscopy, and mass spectrometry. Create and validate artificial intelligence (AI)-based in vitro diagnostic applications. Advance life science data processing and AI models with parallel and cloud computing and FDA Software Validation.
MATLAB for Industrial Automation and Machinery
Industrial Automation and Machinery
Develop embedded control and signal processing applications for industrial and energy-related equipment.
Data-driven and physics-based models can be tuned with real-world data from the operating asset to act as a digital twin. Engineers can use these digital twins for prediction, what-if simulations, anomaly detection, fault isolation, and more. Virtual commissioning allows engineers to identify and eliminate design errors early in the process, decreasing the development and validation time, while reducing risk and potential damage.”
Power Generation and Transmission Equipment
MATLAB and Simulink helps to design control and monitoring algorithms for a wide range of power generation and transmission equipment. Develop and validate algorithms in a safe environment using complex system models that include physical components (mechanical, electrical, hydraulic, etc.), control systems, and fault injection. Detect design errors early and evaluate different control strategies. Deploy code on embedded targets (using microcontrollers or FPGAs), PLCs, or production servers. Optimize equipment design to increase uptime and equipment efficiency.
Machine Builders
From food packaging to metal cutting and injection molding, like production machines use MATLAB and Simulink to address the increasing complexity of their equipment. Building mechatronic models of their systems for desktop simulation and virtual commissioning. Designing and verifying controls and supervisory logic algorithms. Running hundreds of scenarios in simulation without involving prototypes or production systems. Generating real-time code (IEC 61131-3 or C/C++) for deployment on different PLC platforms
Building Automation
MATLAB and Simulink help engineers in developing control and monitoring algorithms for systems such as escalators, elevators, and HVAC systems from design and validation to deployment.
Electric Drives and Automation Components
As industrial automation components (electric drives, sensors, etc.) are getting more sophisticated, MATLAB and Simulink supports in designing control algorithms and to analyze and simulate signals. Engineers can also deploy validated functionality on the components using IEC 61131-3, VHDL®, Verilog®, and C and C++ code generation.
Metals, Materials, and Mining
Metallurgists and process engineers use MATLAB and Simulink to optimize throughput, minimize downtime, and increase safety. They analyze real-time sensor data, model and simulate mining operations, implement control strategies, and leverage artificial intelligence systems.
Automated Material Handling
Engineers in the automated material handling industry use Model-Based Design from equipment design to operation. With MATLAB® and Simulink®, you can: Develop advanced autonomous and control algorithms by systematic use of digital models throughout the development process Improve software quality with automatic generation of real-time code (IEC 61131-3 or C/C++) Optimize and verify machine software in simulation by virtual commissioning Develop and deploy condition monitoring and predictive maintenance software to embedded, cloud, and edge systems
MATLAB for Energy Production and Grid Analytics
Energy Production
Develop and implement models, analyze big data, and automate processes.
Digital transformation in the energy industry helps to anticipate and accelerate cost-effective decisions on sustainable, circular, and new energy processes. MATLAB and Simulink support digital transformation in energy, power, and utility segments with data science, data engineering, high-power computing
Energy Resources
Geoscientists and engineers in the oil and gas industries choose MATLAB and Simulink products to model and optimize drilling equipment, analyze seismic data to determine optimal drilling locations, run Monte-Carlo simulations for valuation and risk assessment, model reservoirs to extend the life of oil and gas reserves and scale their analytics to GPU clusters and the cloud.
Modelling and Simulation
Analyze seismic and wellbore data in multiple domains using image, signal, and wavelet processing algorithms. Large-scale data analysis can be done fast with using computer vision (image and signal processing) and data science (AI, machine learning, and deep learning) with high-power computing (HPC) capabilities.
Process Optimization
MATLAB and Simulink enable rapid testing and assessment of technical and operational processes at subsurface, surface, field, plant, or asset level to optimize production performance, minimize operating costs and downtime, and maximize return on investment.
Interconnectivity
Scientists and engineers use MATLAB to connect with external software applications for rapid design and prototyping of dynamic models to accelerate parameterization, perform sensitivity analysis, and automate process optimization workflows using physics-informed machine learning, advanced control systems, and more.
Chemicals and Materials
Process engineers use MATLAB and Simulink to analyze real-time sensor data, implement control strategies, and create predictive maintenance systems based on big data and machine learning. Develop and implement advanced predictive control (APC) strategies, adopt digitization without depending on data scientists or IT personnel.
Utilities and Energy
To perform system feasibility and grid integration studies using prebuilt functions and apps, acquire and analyze large data sets in real time Develop optimization algorithms using machine learning and deep learning techniques. Develop energy trading and risk management (ETRM) solutions and deploy developed code directly to real-time and embedded systems.
MATLAB for Communications and Electronics Systems
Communications and Electronics Systems
Create, design, simulate, and test algorithms, devices, and communication systems.
MATLAB and Simulink help engineers design and simulate communications systems with greater speed and accuracy. Communications engineers can implement the desired level of model fidelity and run-time performance from within a single environment. With MATLAB they can design, simulate, and prototype complex wireless systems such as 5G and WLAN. Develop algorithms on a unified platform for wireless base station/devices and semiconductor chips combining signal processing, analog/mixed-signal, RF, and antennas.”
Communications
Base station and network engineers use MATLAB and Simulink to design and model end-to-end communications links. Design, simulate, and verify complex wireless systems using industry standards such as 5G and WLAN. Efficiently model advanced channels such as MIMO and analyze the effects of RF impairments on network performance. Prototype, design, and verify on FPGAs and ASICs.
Electronics
Engineers use MATLAB and Simulink product families to design and simulate signal and image processing systems and control systems by capturing algorithms and system models. Evaluate design implementation tradeoffs to build real-time signal processing systems. Develop digital control systems for motors, power converters, and battery systems.
Semiconductors
Integrated Circuit (IC) Design engineers use Model-Based Design to enhance architectural exploration, early verification, and reduce development time and costs. Generate synthesizable RTL code and C/C++, HDL, System C, and IBIS-AMI testbenches. Electronic Design Automation (EDA) workflows, leveraging them as golden reference models, stimuli generators, and validated testbenches, improve the efficiency of analog and mixed-signal designs with automation, advanced reporting, curve fitting, and AI.
Software and Internet
Model-Based System Engineering to design complex EV architectures, optimize systems, model batteries and develop battery management systems (BMS), fuel cell systems (FCS) and develop fuel cell control systems (FCCS), model traction motors and develop Motor Control Units (MCU). Deploy, integrate, and test control algorithms and use data-driven workflows and artificial intelligence (AI) in EV development.
MATLAB for Automotive and Transportation Systems Design
Automotive and Transportation
Design, simulate, and deploy automotive and railway systems.
MATLAB, Simulink and family products advance the design of automated driving perception, planning, and control systems by enabling engineers to gain insight into real-world behavior, reduce vehicle testing, and verify the functionality of embedded software. EV industries use the tools to model, simulate, and develop batteries, motors, and controllers with Model-Based Design. Railway engineering organizations use the tools to develop and maintain rail equipment and meet market requirements for energy efficiency, safety, and availability.
Automotive
Automotive engineers use MATLAB and Simulink to run simulations to evaluate trade-offs and optimize designs. Develop and test perception, planning, and control algorithms. Generate code for prototyping or production, in floating or fixed-point, for MCUs, GPUs, SoCs and FPGA devices. Analyze test fleet and production vehicle data Comply with AUTOSAR and ISO 26262 standards.
Automated Driving
MATLAB, Simulink, and RoadRunner advance the design of automated driving perception, planning, and control systems by enabling engineers to gain insight into real-world behavior, reduce vehicle testing, and verify the functionality of embedded software
Virtual Vehicle:
Virtual vehicles consist of a system-level model that captures the physics and control behaviors of a vehicle like longitudinal dynamics, range, fuel economy, acceleration, and towing capabilities. Virtual vehicles with lateral dynamics focus on braking, suspension, and steering attributes and help to set targets, size components, develop control algorithms, validate software, and test virtually, reducing the need for physical prototypes.
Electric Vehicle
Model-Based System Engineering to design complex EV architectures, optimize systems, model batteries and develop battery management systems (BMS), fuel cell systems (FCS) and develop fuel cell control systems (FCCS), model traction motors and develop Motor Control Units (MCU). Deploy, integrate, and test control algorithms and use data-driven workflows and artificial intelligence (AI) in EV development.
Software-Defined Vehicle
Model-Based Design helps engineering teams tackle these challenges by reusing software across HPC, zonal controllers, and ECUs, meeting safety and quality requirements through automation, shift-left through early validation and software integration in simulation and empowering domain experts to create high-quality software.
Railway Systems
Railway engineers use MATLAB and Simulink to run simulations to evaluate trade-offs and optimize designs, develop and test algorithms for power electronics and motor control, generate code for prototyping or production from simulations, comply with EN 50128 and EN50657 and analyze data from the fleet of railway vehicles to optimize operations and maintenance
MATLAB for Aerospace and Defence Systems Engineering
Aerospace and Defense
Design, simulate, test, and deploy safety and mission critical systems.
Design, simulate, test, and deploy safety and mission critical systems. “Aerospace and Defense (AeroDef) organizations use MATLAB and Simulink as a foundation for digital transformation. Organizations use Model-Based Systems Engineering (MBSE) and Model-Based Design to comply with safety and security aerospace certification standards, aerospace engineers with capabilities that speed the development process and improve communication between teams. During Electronic warfare (EW) systems design tools are used to rapidly prove viability of new technology concepts, eliminate design problems early in the development cycle, and streamline design verification.”
Certification Standards
Model-Based Systems Engineering (MBSE) and Model-Based Design are used to comply with safety, security aerospace certification standards for Requirements management, System architectures, Behavioral modelling and to generate C, C++, VHDL®, and Verilog® code from models.
Space Systems
MATLAB and Simulink provide aerospace engineers with capabilities that speed the development process and improve communication between teams, mission validation in the time domain, run system-level Monte-Carlo simulations using multi-discipline spacecraft models. Analyze spacecraft telemetry and payload data. Design detailed guidance, navigation, and control (GNC) algorithms.
RF Systems
Radar system engineers can perform feasibility analysis, parameterized performance prediction with metrics, resource management, and coverage analysis using 3D terrain. Explore the characteristics of sensor arrays, waveforms to perform link budget analysis and analyze system or software architectures. Subsystem engineers can populate the architectural model with the behavioral models developed in MATLAB or Simulink or C/C++.
Autonomous Systems
Interdisciplinary teams use MATLAB and Simulink as a common integration environment throughout the entire autonomous underwater vehicle workflow which incorporates platform modeling, environment simulation, and autonomy algorithm design. Model-Based Design helps to reduce risk and build confidence in system performance well in advance of the sea trial.
Systems Engineering
MATLAB, Simulink, System Composer, and Requirements Toolbox together create a single environment for authoring descriptive architecture models that seamlessly connect to detailed implementation models. Systems engineers can establish a digital thread to navigate between system requirements, architecture models, implementation models, and embedded software.
Digital Transformation
Integrated digital approach to develop and field complex systems, organizations can achieve goals around digital acquisition, digital engineering, and building a digital workforce. Engineers can create digital twins, a digital thread, and DevSecOps pipelines that work with interconnected digital infrastructures.
Artificial Intelligence
MATLAB and Simulink enables AI integration in the design, development, and operation of complex engineered systems. Engineers and scientists use MATLAB to create better AI datasets, build AI models for domain-specific tasks, and ensure that AI systems meet safety and reliability standards.
Automated Driving
MATLAB, Simulink, and RoadRunner advance the design of automated driving perception, planning, and control systems by enabling engineers to gain insight into real-world behavior, reduce vehicle testing, and verify the functionality of embedded software.
Computational Biology
Computational biologists use MathWorks products to understand and predict biological behavior using data analysis and mathematical modeling. MathWorks products provide a single, integrated environment to support pharmacokinetics (PK), bioinformatics, systems biology, bioimage processing, and biostatistics.
Control Systems
Control system engineers use MATLAB and Simulink at all stages of development – from plant modeling to designing and tuning control algorithms and supervisory logic, all the way to deployment with automatic code generation and system verification, validation, and test.
Deep Learning
With just a few lines of MATLAB code, you can incorporate deep learning into your applications whether you’re designing algorithms, preparing and labeling data, or generating code and deploying to embedded systems.
Electrification
Engineers use MATLAB and Simulink to develop electrical technologies that help increase reliability, improve efficiency, and mitigate climate change, from motor control and battery management for electric vehicles to integrating renewable energy into the power grid.
Enterprise and IT Systems
Integrate with operational systems like C3.ai or AVEVA PI System and display results in dashboards like PowerBI or Tableau. Interoperate with other languages such as Java and Python.
FPGA, ASIC, and SoC Development
Domain experts and hardware engineers use MATLAB and Simulink to develop prototype and production applications for deployment on FPGA, ASIC, and SoC devices. Generate HDL Code for FPGA, ASIC, and SoC development.
