3 条结果 关键词:多层感知机 ×

Improving odorant chemical class prediction with multi-layer perceptrons using temporal odorant spike responses from drosophila melanogaster olfactory receptor neurons.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2016 Bachtiar LR, Newcomb RD, Kralicek AV, Unsworth CP

本研究探讨利用时间序列尖峰数据提高嗅觉生物传感器预测性能的可能性。作者提出一种人工神经网络(ANN),采用最优混合多层感知机(MLP)系统,对果蝇(Drosophila melanogaster)嗅觉受体神经元(DmOrs)的尖峰响应进行分类,以识别化学气味物的类别。所用数据来自6个果蝇嗅觉受体对34种气味物的响应,并提取500 m...

Application of artificial neural networks on mosquito Olfactory Receptor Neurons for an olfactory biosensor.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2013 Bachtiar LR, Unsworth CP, Newcomb RD

二氧化碳(CO2)和1-辛烯-3-醇(1-octen-3-ol)等气味物是冈比亚按蚊(Anopheles gambiae)宿主搜寻行为的重要驱动因素。鉴于蚊类具有强大的嗅觉处理能力,其嗅觉系统可作为人工嗅觉生物传感器的识别基础。本研究利用冈比亚按蚊嗅觉受体神经元(ORN)对挥发性气味物的放电率数据,训练人工神经网络(ANN),将挥发...

Using artificial neural networks to classify unknown volatile chemicals from the firings of insect olfactory sensory neurons.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2011 Bachtiar LR, Unsworth CP, Newcomb RD, Crampin EJ

嗅觉系统能够检测挥发性化学物质,即气味分子或odorants。这些气味分子具有多样的化学结构,并与嗅觉系统受体相互作用。昆虫嗅觉系统提供了直接测量单个嗅觉感觉神经元(OSN)在气味刺激下产生发放率的独特机会,从而利用这些数据辅助化学物质分类。本文证明,可以利用醋蝇(Drosophila melanogaster)OSN阵列的发放率训...