| Summary: | 碩士 === 中原大學 === 電子工程研究所 === 101 === Abstract
Artificial neural network is used to imitate the processes of biological information systems. And it has been widely used in various industries. It has been also presented versatile functionality in different applications. Pattern recognition technology is the key application in neural network which becomes part of our daily lives, such as information security, authentication, medical image processing, intelligent electronic products, etc. In order to realize the architecture of the artificial neural network in circuit forms, a 8x3 non-volatile memory array using non-overlapped implantation nMOSFETs is designed through the 0.25μm CMOS technology. In addition, it is back-proprogated by the memory testing system.
The single-layer feedforward network is used in the this work to achieve the percepttron learning rules. Based on the sample’s target, targets are chosen for evaluating pattern recognition.
In addition, we have compared the hardware of neural network with simulation software. The result of experiment shows that the numbers of training iteration and the training rate of the hardware and the software are similar.
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