Preprocessing of matrix QCM sensors data for the classification by means of neural network

The learning set is composed of 60 sensor reactions for six types of cologne. The neural network correctly classifies 82-86% of independent examples. The usage of the maximum filter with a small window size allows an increase of the classification rate by 3-5%. The best results (86%) are obtained when only first 50 measurements of sensor reaction are used.