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A Pattern Recognition System Using Evolvable Hardware

机译:使用可扩展硬件的模式识别系统

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We describe a high-speed pattern recognition system using Evolvable Hardware (EHW), which can change its own hardware structure by genetic learning in order to adapt best to the environment. The purpose of the system is to show that EHW can work as a recognition device with such robustness for the noise as seen in the recognition systems based on neural networks. The advantage of EHW compared with a neural network is the high processing speed and the readability of the learned result. The readability means that the result is understandable in terms of Boolean functions. In this paper, we describe the architecture, the learning algorithm and the experiment on the pattern recognition system using EHW.
机译:我们描述了一种高速模式识别系统,使用可进化的硬件(EHW),可以通过遗传学习改变其自己的硬件结构,以便适应环境。该系统的目的是表明,EHW可以作为识别装置作为识别设备,其基于神经网络的识别系统中所见的噪声。与神经网络相比,EHW的优点是高处理速度和学习结果的可读性。可读性意味着结果在布尔函数方面是可理解的。在本文中,我们使用EHW描述了模式识别系统的体系结构,学习算法和实验。

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