Fast and effective model order selection method to determine the number of sources in a linear transformation model

This paper formally introduces the method named as RAE (ratio of adjacent eigenvalues) for model order selection, and proposes a new approach combining the recently developed SORTE (Second ORder sTatistic of the Eigenvalues) and RAE in the context for determining the number of sources in a linear transformation model. The underlying rationale for the combination discovered through sufficient simulations is that SORTE overestimated the true order in the model and RAE underestimated the true order when the signal to noise ratio (SNR) was low. Simulations further showed that after the new method, called RAESORTE, was optimized, the true number of sources was almost correctly estimated even when the SNR was -10 dB, which is extremely difficult for any other model order selection methods; moreover, RAE took much less time than SORTE known as computational efficiency. Hence, RAE and RAESORTE appear promising for the real-time and real world signal processing.