CAREER: Computational Models for Sensor-Based Machine Olfaction

职业：基于传感器的机器嗅觉的计算模型

• 批准号: 9984426
• 负责人: Ricardo Gutierrez-Osuna
• 金额: $ 29.97万
• 依托单位: Wright State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-07-01 至 2002-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9984426&HistoricalAwards=false
• 关键词: CAREER; Computational; Models; Sensor; Based

This is the first year of funding of a 4-year continuing award. The PI will focus on the development of a biologically plausible framework for sensor-based machine olfaction (SBMO), with an emphasis on computation, analysis and instrumentation. The specific objectives are: (1) To develop a computational architecture based on neuro-morphic models of the biological olfactory system in order to improve the signal-processing and cognitive capabilities of SBMO; (2) To validate the perceptual plausibility ofthe computational architecture through comparative studies with the "gold standard" for olfactory perception - human-panel sensory analysis; (3) To develop advanced sensor interrogation techniques in order to improve selectivity, sensitivity and robustness of commercial conductivity-based gas sensor arrays. The results will lay the foundations fora new generation of SBMO systems by helping bridge the gap between multivariate chemical sensing and human olfactory perception. Improved analytical capabilities, as a result of advances in both signal processing and sensor instrumentation, will broaden the range of applications for SBM0.

这是为期4年的授予奖励的第一年。 PI将着重于开发基于传感器的机器嗅觉（SBMO）的生物学上合理的框架，重点是计算，分析和仪器。具体目标是：（1）基于生物嗅觉系统的神经形态模型来开发计算体系结构，以提高SBMO的信号处理和认知能力； （2）通过与嗅觉感知的“黄金标准”的比较研究来验证计算架构的知觉合理性 - 人体面板感觉分析； （3）为了提高基于商业电导率的气体传感器阵列的选择性，灵敏度和鲁棒性，以开发高级传感器询问技术。结果将通过帮助弥合多变量化学感应和人类嗅觉感知之间的差距来奠定新一代SBMO系统的基础。由于信号处理和传感器仪器的进步，提高的分析能力将扩大SBM0应用的范围。