Interpolation of complex stationary processes

The problem of minimum mean-square infinite extent interpolation for discrete-time stationary complex stochastic processes is studied. The interpolator consists of linear combinations of samples of the process and of their complex conjugate. The expressions of the interpolator and of the approximation error are derived and various consequences are examined. It is shown in particular that the approximation error may be zero while the interpolation error obtained when using only linear combinations of the samples is maximum.

[1]  Steven Kay,et al.  Some results in linear interpolation theory , 1983 .

[2]  Pascal Chevalier,et al.  Widely linear estimation with complex data , 1995, IEEE Trans. Signal Process..

[3]  Pascal Bondon,et al.  Second-order statistics of complex signals , 1997, IEEE Trans. Signal Process..

[4]  Ian F. Blake,et al.  On a class of processes arising in linear estimation theory , 1968, IEEE Trans. Inf. Theory.

[5]  John A. Stuller,et al.  Linear interpolation lattice , 1991, IEEE Trans. Signal Process..

[6]  Alberto Leon-Garcia,et al.  A fast algorithm for optimal linear interpolation , 1993, IEEE Trans. Signal Process..