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Embedded platform based neural network model online training method

A neural network model and training method technology, applied in biological neural network models, neural learning methods, etc., can solve problems such as process transplantation without training or optimization, and achieve the effect of real-time and intelligent

Inactive Publication Date: 2010-05-12
ZHEJIANG UNIV
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Problems solved by technology

[0004] Although there are embedded applications of neural network intelligent algorithms such as robots and mobile phone handwriting recognition, most of these applications use offline training, and only transplant the trained results to the embedded platform, but do not transplant the training or optimization process to the embedded platform. platform

Method used

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Embodiment Construction

[0049] The present invention will be further described below in conjunction with the accompanying drawings and embodiments, and the purpose and effect of the present invention will become more obvious.

[0050] Such as figure 1 As shown, the system operated by the online training method of the neural network model based on the embedded platform of the present invention is composed of a microcontroller, a memory, a human-computer interaction interface, a communication interface, and a signal input and output interface. Wherein, the microcontroller is respectively connected with the memory, the human-computer interaction interface, the communication interface and the signal input and output interface.

[0051] The human-computer interaction interface includes buttons and a color-screen liquid crystal display, and the buttons and the color-screen liquid crystal display are all connected with a microcontroller. The communication interface includes an RS232 interface, an Ethernet ...

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Abstract

The invention discloses an embedded platform based neural network model online training method which can automatically set relative parameters according to the data characteristics and can set manual parameter simultaneously, thus maximally meeting the requirements of real time and intelligence. The method enables a running system to satisfy multiple functions such as portability, intelligent analysis and the like, overcomes the defect that the previous systems are hard to realize miniaturization and decide relevant training parameters and are complex in operations, and provides a low-cost, portable and high real-time solution for pattern recognition or soft sensing in the complex process of petrochemical.

Description

technical field [0001] The invention relates to an online training method of a neural network model, in particular to an online training method of a neural network model based on an embedded platform. Background technique [0002] With the development of technology and applications, control systems are becoming more and more complex. For difficult-to-control process problems such as multi-input and multi-output, time-varying, nonlinear, and large time-delay, intelligent algorithms such as neural networks and soft sensor technologies must be used to achieve ideal results. However, these complex algorithms are mostly based on large-scale systems such as DCS and FCS, and the system cost is relatively high. The operating environment of the algorithm is also mostly based on platforms such as industrial computers, which are difficult to meet the requirements of embedded and portable. [0003] Embedded platforms and devices are becoming more and more popular, and have the charact...

Claims

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Application Information

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IPC IPC(8): G06N3/02G06N3/08
Inventor 王健伟朱懿峰段俊宋执环
Owner ZHEJIANG UNIV
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