Simulink 用于 HDL 代码生成和验证
*编写 HDL 代码即可探索、实现和验证 FPGA、SoC 或 ASIC 设计。
进行**层设计和探索，之后直接通过 MATLAB® 或 Simulink® 生成并验证 HDL，以用于 FPGA、ASIC 或片上系统 (SoC) 原型或生产项目。
为任意FPGA、ASIC 或 SoC 硬件生成优化且可读的 VHDL® 或 Verilog®
连接系统级设计与子系统级
使用高质量的硬件模型构建硬件子系统，用于数高质量、DSP、无线通信、控制和视觉处理
自动引导转换为**数，或为器件目标器件生成原生浮点运算
直接从 Simulink 和 MATLAB 部署至原型硬件并进行调试
算法模型和测试用例 可复用
Efficient IC Verification
MATLAB and Simulink products enable collaboration and integration of analog and digital design and verification teams, enabling faster and higher-quality IC designs. Engineers can use a single design environment that combines control logic, state machines, and analog and digital components that are traditionally modeled at different levels of fidelity and in different design environments. MATLAB and Simulink allow the reuse of system-level models and test benches through HDL cosimulation, or as SystemVerilog DPI components that can be exported to an EDA verification environment such as Mentor Graphics ModelSim and Questa, Cadence Incisive, and Synopsys® VCS®.
Access and Analyze Data
MATLAB data analysis products let you access, visualize, and analyze data within a single environment. You can interactively explore data, build customized analyses, and share your discoveries with others through reports, published code, 3D visualizations, or as complete applications.
Develop Machine Learning Algorithms
Machine learning algorithms use computational methods to "learn" information directly from data without assuming a predetermined equation as a model. They can adaptively improve their performance as you increase the number of samples available for learning. Machine learning algorithms are used in applications such as speech and facial recognition. They are used in big data applications that have large datasets with many predictors (features) and are too complex for simple parametric models.
探索如何使用 MATLAB 进行大数据、机器学习和生产分析。
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