A fast recursive-least-squares (FRLS) adaptive notch filter (ANF) for cancellation of sinusoidal interference from recorded biomedical signals is investigated. The FRLS ANF is derived by making an approximation to the...
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A fast recursive-least-squares (FRLS) adaptive notch filter (ANF) for cancellation of sinusoidal interference from recorded biomedical signals is investigated. The FRLS ANF is derived by making an approximation to the conventional recursive-least-squares (RLS) ANF for computation economy. It outperforms the commonly adopted least-mean-squares (LMS) ANF, demonstrating a rapid and bandwidth-insensitive initial convergence. A novel application of the FRLS ANF is for the elimination of the tonal artefact in distortion product otoacoustic emission (DPOAE) signals.
One of the most popular applications of IEEE 802.16 network is to serve as a backhaul service for IEEE 802.11 networks. However, the traffic of an IEEE 802.16 connection aggregated from IEEE 802.11 networks fluctuates...
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ISBN:
(纸本)9781612842547
One of the most popular applications of IEEE 802.16 network is to serve as a backhaul service for IEEE 802.11 networks. However, the traffic of an IEEE 802.16 connection aggregated from IEEE 802.11 networks fluctuates. Thus, efficient bandwidth reservation at the subscriber station (SS) is an importance issue. This study proposes a simple and flexible bandwidth reservation scheme at the SS, called multi-stage self-correction bandwidth reservation (MSBR), to make effective use of the bandwidth without violating the QoS requirements for real-time traffic under the proposed cost model. The MSBR scheme introduces the concept of Decision Period for bandwidth reservation to reduce the control message overheads. The proposed method also adopts the RLS algorithm to predict the traffic arrival and applies the MSBR method to capture the traffic dynamics for bandwidth reservation. Simulation results demonstrate that the proposed MSBR scheme utilizes the bandwidth efficiently without violating the QoS requirements of real-time services.
The recently proposed recursive Inverse (RI) algorithm was shown to have a similar mean-square-error (mse) performance as the recursive-least-squares (RLS) algorithm with reduced complexity. The selection of the forge...
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ISBN:
(纸本)9781457702013
The recently proposed recursive Inverse (RI) algorithm was shown to have a similar mean-square-error (mse) performance as the recursive-least-squares (RLS) algorithm with reduced complexity. The selection of the forgetting factor has a significant influence on the performance of the RLS algorithm. The value of the forgetting factor leads to a tradeoff between the stability and the tracking ability. In a system identification setting, both the filter length and a leakage phenomenon affect the selection of the forgetting factor. In this paper, we first analytically show that this leakage phenomenon and the filter length have much less influence on the performance of the RI algorithm. Simulation results, in a system identification setting, validate the theoretical results.
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