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應用於電子鼻系統之連續侷限型波茲曼演算法晶片設計
Thesis

應用於電子鼻系統之連續侷限型波茲曼演算法晶片設計

王仁和
Masters, 國立清華大學, 電機工程學系
2013

Abstract

連續侷限型波茲曼演算法 電子鼻 CRBM eNose
Many portable or implantable microsystems have incorporated sensor arrays for various biomedical applications. The raw sensory signals are usually high-dimensional, noisy, and drifting. To facilitate in-situ diagnosis or to reduce the data for wireless transmission, a low-power, embedded system is demanded for fusing the sensory signals robustly in real time. A probabilistic neural network called the Continuous Restricted Boltzmann Machine (CRBM) has been shown capable of classifying biomedical data reliably. Thus, it is suitable for CRBM to act as a signal pre-processing unit in system. This paper discuss about how to use CRBM to process sensory data of electronic nose system. At first, it makes pilot simulation in software to confirm the capability of CRBM for processing sensory data. Then it will study the method of implementing CRBM into VLSI (Very Large Scale Integration) and integrating with electronic nose system. The chip of CRBM integrating with electronic nose system has been designed and fabricated with the TSMC 0.18μm and 90nm technology provided by TSMC (Taiwan Semiconductor Manufacturing Company). The measurement results proved that the CRBM hardware system can perform good processed results as expected.

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