Improved High Pass Filtering for Passive Optical Networks

Jorgesen, Douglas R.; Marki, C.F.; Esener, Sadik C.

doi:10.1109/lpt.2010.2051144

Cited by 14 publications

(6 citation statements)

References 6 publications

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“…For this reason, the pretreatment process of EMG signal is designed as follows. Firstly, the baseline drift is removed by high-pass filter [16][17][18] (cut-off frequency is 5 Hz). e band-pass filter (the range of band frequency is 5-200 Hz) is used to extract the effective frequency band signal, and then the signal is amplified.…”

Section: Preprocessing Of Surface Electromyography Signal Andmentioning

confidence: 99%

Application Analysis of Wearable Technology and Equipment Based on Artificial Intelligence in Volleyball

Dai

2021

Mathematical Problems in Engineering

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Today, while people’s satisfaction with materials is high, the pursuit of health has begun and sports are becoming increasingly important. Volleyball is a good physical and mental exercise, which helps improve the health of the body. However, excessive exercise usually leads to muscle strain and more serious accidents. Therefore, how to effectively prevent excessive fatigue and sports injuries becomes more and more important. In the past, some methods of exercise fatigue detection were mostly self-assessment through some indicators, which lacked real-time and accuracy. With the advancement of smart technology, in order to better detect sports fatigue, smart wearable technology and equipment are used in volleyball. Firstly, surface electromyography signals (sEMG) are collected through wearable technology and equipment. Secondly, the signal is preprocessed to extract features that are conducive to exercise fatigue assessment. Finally, a motion fatigue detection algorithm is designed to identify and classify features and evaluate the motion status in real-time. The simulation results show that it is feasible to collect ECG signals and EMG signals to detect exercise fatigue. The algorithm has good recognition performance, can evaluate exercise conditions in real-time, and prevent fatigue and injury during exercise.

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Section: Preprocessing Of Surface Electromyography Signal Andmentioning

confidence: 99%

Application Analysis of Wearable Technology and Equipment Based on Artificial Intelligence in Volleyball

Dai

2021

Mathematical Problems in Engineering

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“…Low‐frequency filtering is known to impact the non‐random bit streams [6]. The example PHY‐filters avoided the <50 MHz region to minimise the impact of long consecutive‐bit strings.…”

Section: Impact Of Phy‐filter On 10 Gbit/s Linkmentioning

confidence: 99%

“…For baseband systems in general, flat passbands and well‐shaped high‐frequency cutoffs are design objectives and irregularities in the frequency response are rarely studied [5, 6]. The impact from the triangular RF filters of Fig.…”

Section: Impact Of Phy‐filter On 10 Gbit/s Linkmentioning

confidence: 99%

“…1, a triangular filter with a maximum attenuation at ∼50 MHz followed by a +0.05 dB/MHz ramp will accommodate a wide variety of deployment scenarios. Impact of PHY-filter on 10 Gbit/s link: For baseband systems in general, flat passbands and well-shaped high-frequency cutoffs are design objectives and irregularities in the frequency response are rarely studied [5,6]. The impact from the triangular RF filters of Fig.…”

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confidence: 99%

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Minimising nonlinear Raman crosstalk in future network overlays on legacy passive optical networks

Piehler

2014

Electron. lett.

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There is a desire to overlay future optical access networks onto legacy passive optical networks (PONs) to provide increasingly advanced services by filling empty wavelength bands of legacy gigabit rate PONs. Nonlinear Raman crosstalk from new wavelengths onto legacy RF video services (1550-1560 nm band) and onto the legacy digital downstream at 1490 nm, however, can limit the number and the launch power of new wavelengths. As an example, straightforward physical-layer adjustments at the optical line terminal that increase the number of new, 10 Gbit/s channels launched in the 1575-1580 nm band by a factor of 16 without increasing the Raman penalty on the video signal are illustrated. A physical-layer (RF) filter modifies the on-off-keyed signal feeding each 10 Gbit/s transmitter, suppressing the RF Raman crosstalk on the video signal by 9 dB while incurring a power penalty on each 10 Gbit/s link of <0.5 (2.0) dB with (without) forward error correction. The previous Raman mitigation work used non-standard line-coding to shape the

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“…Unfortunately, the HPF which has the higher low-cutoff frequency compared with the 1st signal spectrum brings about unavoidable signal distortion [13]. Thus, we need trade-off between the noise suppression and the signal distortion.…”

Section: Proposed Broadcast Capable Wdm-pon Based On a Noise-suppressmentioning

confidence: 99%

Noise-suppressed mutually injected Fabry-Perot laser diodes for 10-Gb/s broadcast signal transmission in WDM passive optical networks

Yoo¹,

Kim²,

Seo³

et al. 2013

Opt. Express

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We propose and demonstrate 10-Gb/s broadcast signal transmission in a wavelength-division-multiplexing passive optical network (WDM-PON) by employing a modular-type mutually injected Fabry-Perot laser diodes (MI F-P LDs) as a cost-effective multi-wavelength light source (MWS). We introduce a simple interferometric noise suppression technique with proper electrical filtering to improve transmission performance. The noise suppression doubles the number of supported subscribers with a single MI F-P LDs.

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Improved High Pass Filtering for Passive Optical Networks

Cited by 14 publications

References 6 publications

Application Analysis of Wearable Technology and Equipment Based on Artificial Intelligence in Volleyball

Application Analysis of Wearable Technology and Equipment Based on Artificial Intelligence in Volleyball

Minimising nonlinear Raman crosstalk in future network overlays on legacy passive optical networks

Noise-suppressed mutually injected Fabry-Perot laser diodes for 10-Gb/s broadcast signal transmission in WDM passive optical networks

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