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Biologically inspired large scale chemical sensor arrays and embedded data processing

机译:受生物启发的大规模化学传感器阵列和嵌入式数据处理

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Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: the olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes
机译:生物嗅觉在特异性,响应时间,检测限,编码能力,时间稳定性,鲁棒性,尺寸,功耗和便携性方面均优于化学仪器。这种生物学功能在很大程度上归功于嗅觉途径的独特结构,该结构结合了高度的冗余度,有效的组合编码以及无与伦比的化学信息处理机制。过去十年见证了对嗅觉系统功能基础的计算原语的理解方面的重要进步。欧盟资助的NEUROCHEM项目(Bio-ICT-FET- 216916)开发了新颖的计算范例和具有生物学动机的化学制品,以从生物嗅觉途径中汲取灵感进行化学传感。为了证明这种方法,在模拟嗅觉受体神经元层的聚合物技术中,采用仿生演示器构建了大规模传感器阵列(65K元素),并在与化学传感器接口的嵌入式系统中实现了抽象仿生算法。嵌入式系统集成了嗅觉途径中主要解剖结构单元的计算模型:嗅觉球和脊椎动物的嗅觉皮层(或者昆虫中的触角叶和蘑菇体)。为了在嵌入式处理器中实施,已经执行了抽象阶段,其中其处理能力被算法解决方案捕获。最后,使用具有导航功能的气味机器人在混合化学羽流中测试算法模型

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