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- W1549897978 abstract "An olfaction detection spiking neural network that detects binary odor patterns is analyzed and implemented. This paper presents a new method for inhibiting spiking neural networks by modulating a detection threshold. Interference noise from active odors is measured by a single inhibitory neuron. The inhibition neuron changes the detection threshold to create tolerance for a system with multiple odors present. A digital implementation of the inhibition is simulated. Comparative results prove that threshold modulation reduces false-positive detection error in high noise scenarios where fifteen odors are active simultaneously." @default.
- W1549897978 created "2016-06-24" @default.
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- W1549897978 date "2005-03-21" @default.
- W1549897978 modified "2023-09-26" @default.
- W1549897978 title "Electronic nose inhibition in a spiking neural network for noise cancellation" @default.
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- W1549897978 doi "https://doi.org/10.1109/cibcb.2004.1393944" @default.
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