Fooling a different sniffer

Suppose now that we have two different sniffer spaces, S1 and S2, with odorant vectors dS1(o; c) and dS2(o; c) of dimensions m1 and m2, respectively. Can we digitize an odorant (o; c) in the first sniffer and then produce a mixture of palette odorants such that the second sniffer will be fooled into thinking it to be (o; c)? No such mapping has ever been proposed. For example, the data provided by a single QMB sensor will probably not suffice to predict the response of some MOX sensor. Single sensor eNoses are, however, not realistic. We claim that for reasonable sniffers, with an adequate multitude of sensors, a good mapping can indeed be found. When a sniffer consists of an array of diverse sensors, it is likely to capture the physical information it needs for characterizing a certain odorant. At least in theory, this information is all that is needed in order to predict the response of another sniffer with similar information content. Put differently, finding the mapping g : S1 -> S2 is more likely to be possible when m1 is large, and when the sensors are as diverse as possible. In our ongoing research, S1 is the MosesII eNose, with its 16 different sensors made up of two completely different technologies.

Once this mapping is found, we would read in the input odor in S1, yielding the m1-dimensional odorant vector dS1(o; c), and then compute the mapping into the space S2, yielding the m2-dimensional odorant vector dS2(o; c). This vector would then be used, to fool the second sniffer, S2.using, our experiments show that the space is adequately linear.