磁滞量化器

电路与系统学报 Pub Date : 2000-04-01 DOI:10.1109/ISCAS.1997.608919

K. Jin'no, M. Tanaka

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引用次数: 7

摘要

本文利用互连接神经网络提出了两种类型的量化器。由于神经网络的每个单元都具有滞后特性，这些量化器可以将任何输入信号转换为合适的量化输出。并提出了它在图像处理中的应用，可以进行强度转换。采用面积强度法可以在不使用双电平输出函数的情况下获得高质量的输出图像。

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Hysteresis quantizer

This paper proposes two type quantizers by using mutual connected neural networks. Since each cell of the neural networks has hysteresis properties, these quantizers can convert any input signals into a suitable quantization output. Also, we propose its application for image processing which can be intensity conversion. By using an area intensity method, we can get high quality output images in spite of to use bilevel output function.

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来源期刊

电路与系统学报

自引率

0.00%

发文量

2463