Complex ICA using generalized uncorrelating transform
Signal Processing
On the equivalence of time and frequency domain maximum likelihood estimation
Automatica (Journal of IFAC)
On widely linear Wiener and tradeoff filters for noise reduction
Speech Communication
Augmented second-order statistics of quaternion random signals
Signal Processing
An adaptive approach for the identification of improper complex signals
Signal Processing
| Hi-index | 35.69 |
Circularity is an assumption that was originally introduced for the definition of the probability distribution function of complex normal vectors. However, this concept can be extended in various ways for nonnormal vectors. The first purpose of the paper is to introduce and compare some possible definitions of circularity. From these definitions, it is also possible to introduce the concept of circular signals and to study whether or not the spectral representation of stationary signals introduces circular components. Therefore, the relationships between circularity and stationarity are analyzed in detail. Finally, the theory of linear mean square estimation for complex signals exhibits some connections with circularity, and it is shown that without this assumption, the estimation theory must be reformulated