代码生成和部署

生成台式计算机，移动设备和嵌入式目标的独立应用程序

After you develop your application using音频工具箱™features, you can generate portable C/C++ source code, standalone executables, or standalone applications from your MATLAB^®代码or Simulink^®model。使用代码生成，您可以：

运行你的algorithm在没有MATLAB的机器上or Simulinkinstalled.
Speed up processing while you work in the MATLABor Simulinkenvironment.
Embed your algorithm in hardware.
Incorporate your algorithms into legacy code.

This table compares deployment characteristics ofMATLAB Compiler™和MATLAB Coder™功能。使用此表来决定如何部署MATLAB代码or Simulink model。

部署特征	UsingMATLAB Compiler功能	UsingMATLAB Coder功能
Output	Nonreadable shared libraries.	Portable and readable C source code.
Library dependency	MATLABRuntime。	仅对音频I/O功能的库依赖性：Run Audio I/O Features Outside MATLAB and Simulink。
Supported platforms for deployment	视窗^®,Mac, and Linux^®。	Any platform that supports ANSI^®/ISO^®C/C++ code.
Intellectual property protection	包装代码已加密。	代码未加密。您可以通过生成共享库而不是可读代码来保护您的IP。
算法加速度	Same speed as MATLAB.	根据算法，可能会更快。
MATLAB graphics	万博1manbetx支持的。	Not supported.

To deploy an audio plugin to a digital audio workstation, seeExport a MATLAB Plugin to a DAW。

To deploy a System object™ audio plugin to Simulink, seeConvert Audio Plugin System Objects to Simulink Blocks。

Topics

What is C Code Generation from MATLAB?
Introduces code generation support.
Run Audio I/O Features Outside MATLAB and Simulink
设置系统环境以使用动态库文件进行部署的音频I/O系统对象和块。
识别和显示口头指令在Android Device（万博1manbet万博1manbetxxsimulink支持包适用于Android设备）
This example shows how to use the Simulink® Support Package for Android™ Devices to deploy a deep learning algorithm that recognizes and displays commands spoken through your Android device such as a phone or tablet.

Related Information

Active Noise Control: From Modeling to Real-Time Prototyping
MATLAB编译器产品的适当任务s manbetx 845(MATLAB Compiler)
独立应用(MATLAB Compiler)

Featured Examples

语音命令识别代码生成Raspberry Pi

Deploy feature extraction and a convolutional neural network (CNN) for speech command recognition to Raspberry Pi™. To generate the feature extraction and network code, you use MATLAB Coder™, MATLAB® Support Package for Raspberry Pi Hardware, and the ARM® Compute Library. In this example, the generated code is an executable on your Raspberry Pi, which is called by a MATLAB script that displays the predicted speech command along with the signal and auditory spectrogram. Interaction between the MATLAB script and the executable on your Raspberry Pi is handled using the user datagram protocol (UDP). For details about audio preprocessing and network training, see Speech Command Recognition Using Deep Learning.

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Speech Command Recognition Code Generation with Intel MKL-DNN

在英特尔®处理器上部署功能提取和卷积神经网络（CNN）。为了生成功能提取和网络代码，您可以将MATLAB®编码器和Intel®Math-Matherel库用于深神经网络（MKL-DNN）。在此示例中，生成的代码是MATLAB可执行文件（MEX）函数，该函数由MATLAB脚本调用，该脚本将显示预测的语音命令以及时域信号和听觉频谱图。有关音频预处理和网络培训的详细信息，请参阅使用深度学习的语音命令识别。

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Parametric Audio Equalizer for Android Devices

Use the Single-Band Parametric EQ block and the多体板来自Audio Toolbox™的System Object™以实现参数音频均衡器模型。您可以在主机计算机上运行模型或将其部署到Android设备上。

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Parametric Audio Equalizer for iOS Devices

Use the Single-Band Parametric EQ block and the多体板System object™ to implement a parametric audio equalizer model, that can run on your host computer or an Apple iOS device.

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Audio Effects for iOS Devices

Use System objects™ from Audio Toolbox™ to implement echo and reverberation effects in a Simulink® model. You can run the model on your host computer or deploy it to an Apple iOS device.

开放型号

Multiband Dynamic Range Compression for iOS Devices

使用跨界过滤器块，compressorSystem object™ from the Audio Toolbox™ to implement a multiband dynamic range compressor model. You can run the model on your host computer or deploy it to an Apple iOS device.

开放型号

Generate Standalone Executable for Parametric Audio Equalizer

使用MATLAB CODER™生成一个独立的可执行文件，用于参数均衡，并将其在音频文件上使用。多体板用于均衡算法。该示例允许您使用在MATLAB中运行的用户界面（UI）动态调整过滤器的系数。

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Deploy Audio Applications with MATLAB Compiler

使用MATLAB Compiler™从MATLAB函数创建独立应用程序。该功能实现音频处理算法并通过音频输出设备播放结果。

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带有MATLAB编码器的桌面实时音频加速度

加速使用C代码生成的实时音频应用程序MATLAB Coder。

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