Most approaches in array signal processing assume the signals to be embedded in white noise. However, this assumption is unrealistic in many scenarios, such as statistical shape models. We propose a strategy that can handle colored noise in the detection of the number of sources. We model the source detection as a regression problem and apply information-theoretic criteria to determine the model order of the regression.
The technique is available in MATLAB code in the function nsource_colorednoise.m
In case of questions, suggestions, problems etc. please send an email to
Alma Eguizabal: [email protected]
[1] A. Eguizabal, C. Lameiro, D. Ramírez and P. J. Schreier, “Source enumeration in the presence of colored noise”, to be published in IEEE Signal Processing Letters, February 2019, DOI 10.1109/LSP.2019.2895548
[2] A. Eguizabal, P. J. Schreier and D. Ramírez, “Model-order selection in statistical shape models”, in Proc. of the IEEE International Workshop on Machine Learning for Signal Processing (MLSP), September 2018, https://arxiv.org/abs/1808.00309