Capturing signals without noise and interference while monitoring the maternal abdomen's fetal electrocardiogram (FECG) is a challenging task. This method can provide fetal monitoring for long hours, not harming t...
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Capturing signals without noise and interference while monitoring the maternal abdomen's fetal electrocardiogram (FECG) is a challenging task. This method can provide fetal monitoring for long hours, not harming the pregnant woman or the fetus. Such non-invasive FECG raw signal suffers from various interference sources as the bio-electric maternal potentials include her ECG component. Therefore, a critical step in the non-invasive FECG is to design the filtering of components derived from the maternal ECG. There is an increasing demand for portable devices to extract a pure FECG signal and to detect fetal heart rate (FHR) with precision. Dedicated CMOS architectures enable higher energy efficiency in portable devices. This paper proposes VLSI architectures dedicated to FECG extraction and FHR processing. Fixed-point architectures for the FECG detection exploring the NLMS (normalized least mean square), ipnlms (improved proportional NLMS), and three different division VLSI CMOS architectures are designed herein. An architecture based on the Pan-Tompkins algorithm that processes the FECG for extracting the FHR, extending the functionally of the system, is also proposed. The results show that the NLMS and ipnlms based architectures effectively detect the R-peaks of FECG with a detection accuracy of 92.86% and 93.75%, respectively. The synthesis results shows that our NLMS architecture proposal saves 13.3 % energy, due to a reduction of 279 clock cycles, compared to the state of the art. On the other hand, the ipnlms algorithm results in +0.89% detection accuracy at the price of 42% additional energy consumption w.r.t NLMS.
The tracking performance of adaptive filters is crucially important in practical applications involving time-varying systems. We present an analysis of the tracking performance for ipnlms, one of the best known and be...
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ISBN:
(纸本)9781424442966
The tracking performance of adaptive filters is crucially important in practical applications involving time-varying systems. We present an analysis of the tracking performance for ipnlms, one of the best known and best performing algorithms originally targeted at sparse system identification. We then validate our analytic results in practical simulations for echo cancellation for sparse and dispersive time-varying unknown echo path systems. These results show the analysis to be highly accurate in all the cases studied.
Due to the nature of an acoustic enclosure, the early part (i.e., direct path and early reflections) of the acoustic echo path is often sparse while the late reverberant part of the acoustic path is normally dispersiv...
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ISBN:
(纸本)9781457705397
Due to the nature of an acoustic enclosure, the early part (i.e., direct path and early reflections) of the acoustic echo path is often sparse while the late reverberant part of the acoustic path is normally dispersive. In order to account for this structure within the acoustic impulse response when performing acoustic echo cancellation, we propose an adaptive filter that consists of two time-domain partition blocks, with adaptive block partitioning, such that different adaptive algorithms can be used for each block. Specifically, the improved proportionate normalized least-mean-square (ipnlms) algorithm is used. Simulation results show that the proposed variable length partitioned block ipnlms (VLPB-ipnlms) algorithm works well in both sparse and dispersive circumstances and in practical applications involving time-varying systems.
The tracking performance of adaptive filters is crucially important in practical applications involving time-varying systems. We present an analysis of the tracking performance for ipnlms, one of the best known and be...
详细信息
ISBN:
(纸本)9781424442959;9781424442966
The tracking performance of adaptive filters is crucially important in practical applications involving time-varying systems. We present an analysis of the tracking performance for ipnlms, one of the best known and best performing algorithms originally targeted at sparse system identification. We then validate our analytic results in practical simulations for echo cancellation for sparse and dispersive time-varying unknown echo path systems. These results show the analysis to be highly accurate in all the cases studied.
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