Fig. 3.

Random receptor arrays with a suitable mean sensitivity $\overline{S}$ and distribution width λ can transmit information about both odor concentration and composition. (A) Information I for lognormally distributed sensitivities as a function of the mean $\overline{S}$ and width λ of the distribution. The shown mean of I was calculated from Eqs. 1−3 using Monte Carlo sampling of 32 realizations per point. The orange line marks the optimum given by Eq. 9. (B) Mean sensitivity $\overline{S}$ for different average mixture sizes s. Numerical optimizations over general sensitivity matrices (symbols; mean $\pm$ SD; 64 samples) are compared with lognormally distributed matrices (solid line, Eq. 9) with $\mathit{\lambda }=1.73$, equal to the mean of the numerical data. Additional parameters in A and B are the same as in Fig. 1.