Model of Neuromorphic Odorant-Recognition Network

We propose a new model for neuromorphic olfactory analyzer based on memristive synapses. The comprises layer of receptive neurons that perceive various odors and “decoder” recognize these odors. It is demonstrated connecting layers with synapses enables the training to two types odorants varying concentrations. In absence such synapses, does not exhibit specificity in recognizing odorants. recognition ’odorant’ occurs through neural activity group decoder have acquired odorant learning process. proposed phenomenological showcases potential use synapse practical applications.