Abstract
This paper proposed a new normalized transform domain conjugate gradient algorithm (NT-CGA), which applies the data independent normalized orthogonal transform technique to approximately whiten the input signal and utilises the modified conjugate gradient method to perform sample-by-sample updating of the filter weights more efficiently. Simulation results illustrated that the proposed algorithm has the ability to provide a fast convergence speed and lower steady-error compared to that of traditional least mean square algorithm (LMSA), normalized transform domain least mean square algorithm (NT- LMSA), Quasi-Newton least mean square algorithm (Q-LMSA) and time domain conjugate gradient algorithm (TD-CGA) when the input signal is heavily coloured.
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Zou, Y., Chan, S.C., Ng, T.S. et al. Transform domain conjugate gradient algorithm for adaptive filtering. J. of Electron.(China) 17, 69–76 (2000). https://doi.org/10.1007/s11767-000-0024-x
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DOI: https://doi.org/10.1007/s11767-000-0024-x