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|Title:||Adaptive noise subspace estimation algorithm with an optimal diagonal-matrix step-size|
|Keywords:||Adaptive signal processing|
Noise subspace estimation
|Citation:||Yang, L., Attallah, S. (2007). Adaptive noise subspace estimation algorithm with an optimal diagonal-matrix step-size. IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation : 584-588. ScholarBank@NUS Repository. https://doi.org/10.1109/SIPS.2007.4387614|
|Abstract:||In this paper, we propose a new optimal diagonal-matrix stepsize for the fast data projection method (FDPM) algorithm. The proposed step-sizes control the decoupled subspace vectors individually as compared to conventional methods where all the subspace vectors are multiplied by the same step-size value (scalar case). Simulation results show that FDPM with this optimal diagonal-matrix step-size outperforms the original algorithm as it offers faster convergence rate, smaller steady state error and smaller orthogonality error simultaneously. The proposed method can easily be applied to other subspace algorithms as well. © 2007 IEEE.|
|Source Title:||IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation|
|Appears in Collections:||Staff Publications|
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