Abstract

In the literature, there exists a number of blind signal recovery algorithms that are implemented as stochastic gradient descent (SGD)-based adaptive schemes. SGD typically has low complexity at the expense of slower convergence. On the other hand, packet-based data transmission in many practical digital communication systems makes it attractive to develop steepest descent (SD) implementation in order to speed-up convergence. This work aims at developing SD implementation of several well-known blind signal recovery algorithms for multi-channel equalisation and source separation. The authors SD formulation is more amenable to additional parametric and signal subspace constraint for faster convergence and superior performance.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.