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We create a spiking neural network of Integrate and Fire neurons with spike frequency adaption based on parameters adjusted for our e-nose device, and investigate the use of this model for odor classification. Addition of spike frequency adaptation term brings the model closer to the response of the olfactory system. Data from Cyranose 320, a polymer based 32-sensor array, is used to test the system...
A new BP neural network is introduced and at the same time, its' structure, feature and principium are also expatiated. In order to approach compensate the effects of improves non-linearity, a BP neural network model is set up and trained in this paper. The test result indicates that: this method is practical and dependable in the field of salinity modeling, has a good applied foreground.
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