Authors:
B. Dugnol
;
C. Fernández
;
G. Galiano
and
J. Velasco
Affiliation:
Universidad de Oviedo, Spain
Keyword(s):
Time-frequency distribution, instantaneous frequency, signal separation, noise reduction, chirplet transform, partial differential equation, population counting.
Related
Ontology
Subjects/Areas/Topics:
Acoustic Signal Processing
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Informatics in Control, Automation and Robotics
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
;
Speech Recognition
;
Time and Frequency Response
;
Time-Frequency Analysis
Abstract:
We use signal and image theory based algorithms to produce estimations of the number of wolves emitting howls or barks in a given field recording as an individuals counting alternative to the traditional trace collecting methodologies. We proceed in two steps. Firstly, we clean and enhance the signal by using PDE based image processing algorithms applied to the signal spectrogram. Secondly, assuming that the wolves chorus may be modelled as an addition of nonlinear chirps, we use the quadratic energy distribution corresponding to the Chirplet Transform of the signal to produce estimates of the corresponding instantaneous frequencies, chirprates and amplitudes at each instant of the recording. We finally establish suitable criteria to decide how such estimates are connected in time.