Robustness of narrowband DOA algorithms with respect to signal bandwidth
Signal Processing
Partial likelihood for online order selection
Signal Processing - Special issue: Information theoretic signal processing
Model order selection in multi-baseline interferometric radar systems
EURASIP Journal on Applied Signal Processing
Theoretical Analysis and Comparison of Several Criteria on Linear Model Dimension Reduction
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Non-parametric detection of the number of signals: hypothesis testing and random matrix theory
IEEE Transactions on Signal Processing
MMSE-based MDL method for robust estimation of number of sources without eigendecomposition
IEEE Transactions on Signal Processing
Sinusoidal order estimation using angles between subspaces
EURASIP Journal on Advances in Signal Processing
Statistical performance analysis of MDL source enumeration in array processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A theoretical investigation of several model selection criteria for dimensionality reduction
Pattern Recognition Letters
| Hi-index | 35.70 |
A new framework is presented for the analysis of the performance of detection methods, such as AIC and MDL, which are based on the eigenvalues of the sample covariance matrix. It is shown that theoretical analysis of the probabilities of overestimation and underestimation can be much more conveniently carried out via a proposed, particularly simple, sequence of statistics. Also, the breakdown of these detection methods in the presence of model nonidealities is explored by theory, simulations, and experimentation with real array data. For example, theoretical arguments are given to demonstrate the high degree of sensitivity of the detectors to unknown deviations of the noise from whiteness