A combined Kalman filter and natural gradient algorithm approach for blind separation of binary distributed sources in time-varying channels

A combined Kalman filter (KF) and natural gradient algorithm (NGA) approach is proposed to address the problem of blind source separation (BSS) in time-varying environments, in particular for binary distributed signals. In situations where the mixing channel is nonstationary, the performance of the...

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Bibliographic Details
Main Authors: Maria G. Jafari, H.W. Seah, Jonathon Chambers
Format: Default Conference proceeding
Published: 2001
Subjects:
Mechanical engineering not elsewhere classified
Kalman filters
Filtering theory
Gradient methods
Learning systems
Mean square error methods
Time-varying channels
Tracking filters
Mechanical Engineering not elsewhere classified
Online Access:https://hdl.handle.net/2134/5820
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