鲁棒微阵列图像分析与识别的VLSI仿生微系统

W. Fang, Jaw-Chyng L. Lue
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引用次数: 0

摘要

开发了一种用于实时、现场、鲁棒图像分析和识别的VLSI仿生微系统。提出了一种新的基于s型对数传递函数的人工神经网络学习算法。结果表明,与传统的s型神经网络相比,训练后的新神经网络能更好地识别低荧光模式。为计算荧光信号相对强度的对数,设计了一种差分对数成像芯片。设计、制作了单轨对数电路和原型人工神经网络芯片,并对其进行了表征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VLSI Bio-Inspired Microsystem for Robust Microarrray Image Analysis and Recognition
A VLSI bio-inspired microsystem for real-time, on-site, robust image analysis and recognition has been developed. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.
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