Abstract
Applying the convex cost function Lc: to the blind deconvolution of general non-minimum phase AR(u) models is studied.A simple and realizable constraint is proposed for the L^ deconvolution.With this constraint, except for a gain.the model parameter is the unique solution of the L:o deconvolution.The strong consistency of the estimator of the model parameter defined by the sample version of L^ norm is presented.An algorithm is suggested for the iterative computation of the estimator.Simulation examples show the proposed approach works well for apprepriate blind equalization problems.
| Original language | English (US) |
|---|---|
| Journal | European Signal Processing Conference |
| State | Published - 2015 |
| Event | 8th European Signal Processing Conference, EUSIPCO 1996 - Trieste, Italy Duration: Sep 10 1996 → Sep 13 1996 |
Bibliographical note
Funding Information:∑∞ ck < ∞, which, in communications, describes the k=−∞ intersymbol interference, (ii) the input signal {xk} is a zero-mean i.i.d. random sequence. Denote c={ck,-∞<k<∞}. It is assumed that there exists d={dk, ∞<k<∞ },which is called the inverse filter of c, such that d⊗c=δ, where ⊗ means convolution and δ is a delta sequence. In the most general case, {ck} and the probability distribution of xk are unknown. The blind deconvolution problem for (1) is to estimate both of the input sequence {xn}, and the system response {ck}. Numerous approaches have been developed to solve the blind deconvolution problem. One approach is based on ________________________________________ This work was supported in part by the BMDO/IST program managed by the Office of Naval Reseach under Contract N00014-92-J-1911.
Publisher Copyright:
© 2015 European Signal Processing Conference, EUSIPCO. All rights reserved.