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MathWorks application deployment products increase the benefit of MATLAB® to your organization by allowing you to share the work you do in MATLAB with people who do not have access to MATLAB. You can share with internal colleagues and decision makers, or external collaborators and clients.
Your MATLAB based programs can be deployed as standalone applications, add-ins for Microsoft® Excel®, and software components that can be integrated into web and enterprise applications. You can deploy any MATLAB program covering a range of industries and applications such as data science, semiconductor/electronics, manufacturing systems, image processing, aerospace/defense, and financial services.
All applications and components are encrypted to protect your intellectual property and can be shared royalty free.
When compared with manually recoding algorithms, deploying your MATLAB applications and components provides advantages, such as:
Domain experts can maintain ownership of ideas, algorithms, and applications.
Software developers have the flexibility to integrate a common algorithm with different programming languages and platforms.
Organizations gain efficiency by avoiding time consuming and error prone recoding, as well as easily adopting algorithm improvements throughout the application’s lifecycle.
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Rapid prototyping provides a fast and inexpensive way for control and ** processing engineers to verify designs early and evaluate design tradeoffs. MathWorks rapid prototyping products automate much of the time-consuming work involved by enabling you to:
Test new system designs and algorithms on hardware in real time
Perform design iterations in minutes rather than weeks
Focus on innovation
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访问无处不在的数据
设备数据可被结构化或非结构化,它们存储于诸如本地文件、云(例如 AWS® S3、Azure® Blob)、数据库以及历史数据等多种源中。无论您的数据在哪里,您都可以使用 MATLAB 来获取。当您没有足够的故障数据时,可以通过输入信号故障,从机器设备上的 Simulink 模型来生成故障数据,并对系统故障动态进行建模。
整理和探索您的数据以实现简化
数据是散乱的。使用 MATLAB,您可以对数据进行预处理、降维处理并提取特征。
对不同采样率的数据进行调整,并说明缺失值和异常值。
使用的信号处理技术移除杂点、筛选数据并分析瞬态或变化的信号。
使用统计和动态方法进行特征提取和选择,以简化数据集并减少预测模型的过度拟合。
使用机器学习检测和预测错误
运用分类、回归和时序建模技术确定故障根源并预测故障时间。
交互式探查并选择重要的变量来估算 RUL 或对故障模式进行分类。
使用内置函数训练、比较和验证多个预测模型。
计算并可视化置信区间以量化预测中的不确定性。
在生产系统中部署算法
通过在嵌入式设备和企业 IT/OT 系统上实施 MATLAB 算法,缩短响应时间,减少传输的数据,并立即提供结果给车间操作员。
通过使用 MATLAB 和 Simulink 为目标资产和边缘设备自动生成 C/C ++代码来摆脱手动编码。
在含生产服务器的云上扩展 MATLAB 分析,并与 Spotfire、 PI Server 及其他平台集成。
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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.
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