NosEE is Number of Source estimate by Eigenvalue Error. Reference Authors: Soosan Beheshti (soosan@ee.ryerson.ca) and Saba Sedghizadeh CITE: "Number of Source Signal Estimation by the Mean Squared Eigenvalue Error." IEEE Transactions on Signal Processing 66.21 (2018): 5694-5704. https://ieeexplore.ieee.org/document/8466044 Website: https://www.ee.ryerson.ca/~soosan/ Code Developement: Saba Sedghizadeh & Younes Sadat-Nejad Contact Info: soosan@ee.ryerson.ca , seyedyouns.sadatneja@ryerson.ca, Copy right April 2019
Detection of the number of source signals (NoSS) in the presence of additive noise is considered. We present a new approach denoted by themean squared eigenvalue error (MSEE).The MSEE is the mean squared error between the desired noise-free eigenvalues and the available estimated eigenvalues. The approach investigates and analyzes the probabilistic distribution of the available eigenvalue estimates and revisits proper thresholding of these sorted values. The optimum NoSS is provided by minimizing the MSEE. A probabilistic worst-case technique is proposed to estimate the value of the MSEE by using only the available data. It is shown that the proposed method is consistent as the data length increases. It is also shown that the method is consistent as the signal-to-noise ratio (SNR) increases. Simulation results illustrate advantages of the MSEE over competing approaches and confirm effectiveness and robustness of theMSEE even in low-SNR or small sample size scenarios.