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MATLAB® and Simulink® enable automotive engineering organizations to accelerate vehicle development processes and to deliver vehicles that meet market requirements for safety, comfort, fuel economy, and performance.
Automotive engineers use MATLAB and Simulink to:
Run simulations to evaluate trade-offs and optimize designs
Develop and test perception, planning, and control algorithms
Validate requirements early through rapid prototyping
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 and Advanced Driving Assistance Systems (ADAS)
Use MATLAB and Simulink to accelerate the development of automated driving functions including perception, planning, and control functions. Run simulations in Simulink to test, integrate, and tune these functions using programmatically generated scenes and maximize test coverage across various road, traffic, and environmental conditions without expensive prototype vehicles.
MATLAB® and Simulink® products for Model-Based Design and technical computing are the industry-standard tools for designing, implementing, and testing air, space, naval, and land systems. Aerospace and defense companies worldwide rely on these products in major programs, such as the F-35 Joint Strike Fighter and Mars Exploration Rover, as well as for unmanned aerial vehicles and advanced wireless systems, such as software defined radio (SDR).
Model-Based Design with MATLAB and Simulink is a modular development approach that enables engineering teams to move from internal research and development (IRAD) to design and implementation in a single environment. Companies are using this approach to:
Mitigate program risk by sharing system specifications, analysis, and test data
Reduce costly rework through early simulation of design
Promote reuse by interfacing with existing tools, simulations, and legacy software
Leverage new technologies by moving directly from IRAD to production
Research emerging technologies such as cyber-physical systems
Model-Based Design enables medical device engineers to introduce and integrate agile approaches into their existing software development workflows by cleanly separating the design phase from the implementation steps.
Using Model-Based Design, you can:
Model and simulate algorithms and entire systems before implementation
Verify and validate the designs thoroughly at a higher-level abstraction
Prototype design and create proofs-of-concept by automatically generating C or HDL code
Produce customizable reports that can be used as evidence of regulatory compliance
Prove your code is safe under all possible run-time conditions using static analysis
MATLAB 实现深度学习
设计、构建和可视化卷积网络
只需要几行 MATLAB® 代码,无需成为,您就能构建深度学习模型。了解如何使用 MATLAB 帮助您执行深度学习任务。
易于访问新的模型,包括 GoogLeNet、 VGG-16、 VGG-19、AlexNet、ResNet-50、ResNet-101 和 Inception-v3
。
加速 NVIDIA® GPU、云和数据中心资源上的算法,而无需编程。
使用 MATLAB 应用程序和可视化工具,创建、修改和分析复杂的深度网络架构。
使用应用程序自动进行图像、视频和音频数据的真实值 (ground-truth) 标注。
处理来自 Caffe 和 TensorFlow-Keras 的模型。
MATLAB 支持 ONNX™,所以您可以使用 PyTorch 和 MxNet 之类的框架与同事协作。
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