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: 0229598
• 负责人: Ricardo Gutierrez-Osuna
• 金额: --
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0229598&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.

这是一个为期四年的持续奖励的第一年。PI将侧重于为基于传感器的机器嗅觉（SBMO）开发生物学上合理的框架，重点是计算、分析和仪器仪表。具体目标是：(1)开发基于生物嗅觉系统神经形态模型的计算架构，以提高嗅觉系统的信号处理和认知能力；(2)通过与嗅觉感知的“黄金标准”——人面板感官分析的比较研究，验证计算架构的感知合理性；(3)开发先进的传感器询问技术，以提高商用电导率气体传感器阵列的选择性、灵敏度和鲁棒性。该结果将为新一代SBMO系统奠定基础，帮助弥合多元化学传感与人类嗅觉感知之间的差距。由于信号处理和传感器仪器的进步，分析能力的提高将扩大SBM0的应用范围。