Explainability of Neural Networks for Symbol Detection in Molecular Communication Channels
收藏DataCite Commons2023-04-27 更新2025-04-16 收录
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https://ieee-dataport.org/documents/explainability-neural-networks-symbol-detection-molecular-communication-channels
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资源简介：
This data set is from a macroscale molecular communication testbed and provides a set of experimental measurement data. The molecules used are composed of a diluted alcoholic solution, i.e., ethanol molecules. We mixed four parts of water with one part ethanol, with the mass ratio 1/4. The molecules are released by a mechanism at the transmitter side, propagate through the free-space channel, and can be detected at the receiver side with a commercial-off-the-shelf alcohol sensor. Every 0.1 seconds, the current concentration of the ethanol molecules on the receiver side is measured. The information is consequently encoded into temporal sequences (here the temporal concentration of the ethanol molecules). Furthermore, the dataset contains the Matlab processing code.
提供机构：
IEEE DataPort
创建时间：
2023-04-27
