A 54dB-DR 1-GHz-bandwidth continuous-time low-pass filter with in-band noise reduction

2013 ◽  
Author(s):  
M. De Matteis ◽  
S. D'Amico ◽  
G. Cocciolo ◽  
M. De Blasi ◽  
A. Baschirotto
Keyword(s):  
Noise Reduction ◽  
Continuous Time ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Band Noise ◽  
Low Pass

Design of Programmable Wideband Low Pass Filter with Continuous-Time/Discrete-Time Hybrid Architecture

2017 ◽  
Vol E100.C (10) ◽  
pp. 858-865 ◽  
Author(s):  
Yohei MORISHITA ◽  
Koichi MIZUNO ◽  
Junji SATO ◽  
Koji TAKINAMI ◽  
Kazuaki TAKAHASHI
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
Hybrid Architecture ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

scholarly journals Noise Reduction Analysis of Radar Rainfall Using Chaotic Dynamics and Filtering Techniques

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Soojun Kim ◽  
Huiseong Noh ◽  
Narae Kang ◽  
Keonhaeng Lee ◽  
Yonsoo Kim ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Correlation Coefficient ◽  
Standard Error ◽  
Rainfall Series ◽  
Radar Rainfall ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Filtering Technique ◽  
Filtering Techniques

The aim of this study is to evaluate the filtering techniques which can remove the noise involved in the time series. For this, Logistic series which is chaotic series and radar rainfall series are used for the evaluation of low-pass filter (LF) and Kalman filter (KF). The noise is added to Logistic series by considering noise level and the noise added series is filtered by LF and KF for the noise reduction. The analysis for the evaluation of LF and KF techniques is performed by the correlation coefficient, standard error, the attractor, and the BDS statistic from chaos theory. The analysis result for Logistic series clearly showed that KF is better tool than LF for removing the noise. Also, we used the radar rainfall series for evaluating the noise reduction capabilities of LF and KF. In this case, it was difficult to distinguish which filtering technique is better way for noise reduction when the typical statistics such as correlation coefficient and standard error were used. However, when the attractor and the BDS statistic were used for evaluating LF and KF, we could clearly identify that KF is better than LF.

A 2nd-Order Continuous Time Delta-Sigma Modulator for Photoplethysmography Analog Front-End

2020 ◽  
Author(s):  
Eka Fitrah Pribadi ◽  
Rajeev Kumar Pandey ◽  
Paul C.-P. Chao
Keyword(s):  
Transfer Function ◽  
Continuous Time ◽  
Supply Voltage ◽  
Signal To Noise Ratio ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Delta Sigma Modulator ◽  
Delta Sigma ◽  
Low Pass ◽  
Order Continuous

Abstract A brief presents a 2nd order continuous-time delta-sigma modulator (CT-DSM) using a low pass filter to reduce the slew rate requirement of the output swing of the first integrator. By adding the low pass filter, the desired transfer function of the CT-DSM is altered. Thus a feed-forward based compensation circuit is introduced to transform the altered transfer function to the original condition. The CT-DSM is designed with a bandwidth of 100 Hz to satisfy the requirement of photoplethysmogram (PPG) detection. The CT-DSM is simulated using CMOS 180 nm technology with the layout area 460 μm × 460 μm. The circuit uses a 1.8 V supply voltage and consumes 35.61 μW. The signal-to-noise ratio of the CT-DSM is 101.2 dB, while the SFDR is 99.1 dB.

scholarly journals Measurement Accuracy Enhancement via Radio Frequency Filtering in Distributed Brillouin Sensing

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2878 ◽  
Author(s):  
Cheng Feng ◽  
Stefan Preussler ◽  
Jaffar Emad Kadum ◽  
Thomas Schneider
Keyword(s):  
Radio Frequency ◽  
Noise Reduction ◽  
Measurement Accuracy ◽  
Signal To Noise Ratio ◽  
Rf Filters ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Optical Time ◽  
Rf Signal

In this article, we demonstrate the noise reduction and signal to noise ratio (SNR) enhancement in Brillouin optical time-domain analyzers (BOTDA). The results show that, although the main noise contribution comes from the Brillouin interaction itself, a simple low pass filtering on the detected radio frequency (RF) signal reduces remarkably the noise level of the BOTDA traces. The corresponding SNR enhancement depends on the employed cut-off frequency of the low pass filter. Due to the enhancement of the SNR, a mitigation of the standard deviation error of the Brillouin frequency shift (BFS) has been demonstrated. However, RF filters with low cut-off frequency could lead to distortions on the trace signals and therefore detection errors on a non-uniform BFS. The trade-off between the noise reduction and the signal distortion as well as an optimal cut-off frequency are discussed in detail.

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