Advance in the bat acoustic identification systems based on the audible spectrum using nonlinear dynamics characterization

Frequential and time lineal parameters have shown a good performance in the recognition of bat species and nowadays there are many works which obtain those characteristics very accurately. However, it is necessary to move forward and test the capabilities of other characterizations on bioacoustics successfully used in other fields. In this work the chaos theory, which is an area of nonlinear dynamics systems, is applied to bat acoustic identification. The database used in the evaluation consists of 50 bat calls of seven different classes extracted from a previous work. The combinations of linear and nonlinear parameters have resulted in an average error of 1.8%, improving the accuracy in 0.42%. The differences to identify between the most difficult species and the easiest ones have been reduced.