matlab软件学习 matlab 2020b 专业培训

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Matlab在机电一体化的应用
Developing mechatronic systems requires integrating mechanical, electrical, control, and embedded software subsystems. Model-Based Design and MathWorks products enable you to design and simulate all of these domains in a single environment.
Through desktop and real-time simulations, you can:
Predict and optimize system performance
Understand and manage complex system interactions
Detect design inefficiencies and integration errors early during development
Verify and test mechatronic systems such as motor control using fewer hardware prototypes.
Eliminate manual coding errors by automatically generating code from the simulation model

为什么使用 MATLAB 实现深度学习？
互操作性
不再有框架基于 MATLAB 还是 Python 的选择题。使用 ONNX 导入和导出功能，MATLAB 支持与开源深度学习框架的互操作性。使用 MATLAB 工具的大意义在于——访问 Python 中没有的功能与预置函数及应用程序。
预处理应用程序
快速开始网络训练。使用特定领域应用程序快速预处理音频、视频和图像数据集。使用 Deep Network Designer 应用程序创建复杂的网络架构，或修改预训练网络以进行迁移学习，在训练之前可视化、检查并修复问题。
多平台部署
可随处部署深度学习模型，包括 CUDA、C 代码、企业系统或云。若在意性能，您可以利用 Intel® (MKL-DNN)、NVIDIA（TensorRT、cuDNN）和 ARM® (ARM Compute Library) 优化库生成代码，创建具有高性能推理速度的可部署模型。

Matlab在数字信号处理中的应用
Signal processing is essential for a wide range of applications, from data science to real-time embedded systems. MATLAB® and Simulink® products make it easy to use ** processing techniques to explore and analyze time-series data, and they provide a unified workflow for the development of embedded systems and streaming applications.
With MATLAB and Simulink ** processing products, you can:
Acquire, measure, and analyze **s from many sources.
Design streaming algorithms for audio, smart sensor, instrumentation, and IoT devices.
Prototype, test, and implement DSP algorithms on PCs, embedded processors, SoCs, and FPGAs.
Signal processing is essential for a wide range of applications, from data science to real-time embedded systems. MATLAB® and Simulink® products make it easy to use ** processing techniques to explore and analyze time-series data, and they provide a unified workflow for the development of embedded systems and streaming applications.
With MATLAB and Simulink ** processing products, you can:
Acquire, measure, and analyze **s from many sources.
Design streaming algorithms for audio, smart sensor, instrumentation, and IoT devices.
Prototype, test, and implement DSP algorithms on PCs, embedded processors, SoCs, and FPGAs.
Signal Analysis for Everyone
MATLAB and ** processing products help you analyze **s from a range of data sources. You can acquire, measure, transform, filter, and visualize **s without being an expert in ** processing theory. You can apply ** processing tools to:
Preprocess and filter **s prior to analysis.
Explore and extract features for data analytics and machine learning applications.
Analyze trends and discover patterns in **s.
Visualize and measure time and frequency characteristics of **s.

MATLAB GPU 计算支持可适用
于运行NVIDIA CUDA 的GPU
在支持 NVIDIA CUDA 的GPU 上执行 MATLAB 计算
*成为 CUDA® 程序员，MATLAB® 即可让您能够使用 NVIDIA® GPU 来加速 AI、深度学习和其他计算密集型分析。使用 MATLAB 和 Parallel Computing Toolbox™，您可以：
直接在 MATLAB 中调用 NVIDIA GPU，有 500 多个内置函数可供使用。
使用 MATLAB worker 和 MATLAB Parallel Server™ 访问台式机、计算集群和云上的多GPU。
使用 GPU Coder™ 直接从 MATLAB 生成 CUDA 代码，以便部署到数据中心、云和嵌入式设备。
使用 GPU Coder 从 MATLAB 生成 NVIDIA TensorRT™ 代码，实现低延迟和高吞吐量的推理。
将 MATLAB AI 应用程序部署到配备 NVIDIA GPU的数据中心，与使用 MATLAB Production Server™ 的企业系统集成。