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In most olfactory systems, the first processing step consists of a high convergence, i.e. many ORNs with similar odor-response profiles converge on few PNs.
Why is high convergence important?
However, if the culture you have is not the one you want, high convergence will make it harder to change.
It could reach the satisfied solutions with high convergence speed in an acceptable computational time.
The proposed method has a truly low computational cost accompanied by high convergence rate.
These results show proposed system produces high convergence rate and low test errors.
The empirical results show that model fitting work well, and have high convergence validity.
Because of the very high convergence rates, these methods are suitable for obtaining accurate solutions.
The results show that the proposed method can successfully obtain the near-optimal solutions with high convergence rate.
These results show that proposed system in this paper produces high convergence rate and low test error.
Error analysis of the approximate solution is studied using the absolute error and high convergence is achieved.
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