標題: Bio-inspired microsystem for robust genetic assay recognition
作者: Lue, Jaw-Chyng
Fang, Wai-Chi
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
公開日期: 2008
摘要: A compact integrated system-on-chip (SoC) architecture solution for robust, real-time, and on-site genetic analysis has been proposed. This microsystem solution is noise-tolerable and suitable for analyzing the weak fluorescence patterns from a PCR prepared dual-labeled DNA microchip assay. In the architecture, a preceding VLSI differential logarithm microchip is designed for effectively computing the logarithm of the normalized input fluorescence signals. A posterior VLSI artificial neural network ( ANN) processor chip is used for analyzing the processed signals from the differential logarithm stage. A single-channel logarithmic circuit was fabricated and characterized. A prototype ANN chip with unsupervised winner-take-all (WTA) function was designed, fabricated, and tested. An ANN learning algorithm using a novel sigmoid-logarithmic transfer function based on the supervised backpropagation ( BP) algorithm is proposed for robustly recognizing low-intensity patterns. Our results show that the trained new ANN can recognize low-fluorescence patterns better than an ANN using the conventional sigmoid function. Copyright (C) 2008 J.-C. Lue.
URI: http://hdl.handle.net/11536/9991
http://dx.doi.org/10.1155/2008/259174
ISSN: 1110-7243
DOI: 10.1155/2008/259174
期刊: JOURNAL OF BIOMEDICINE AND BIOTECHNOLOGY
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