Research on PTP Clock Synchronization in IP

2014 ◽  
Vol 1079-1080 ◽  
pp. 762-765
Author(s):  
Hai Dong Zou ◽  
Liang Qian
Keyword(s):  
Time Synchronization ◽  
Clock Synchronization ◽  
Random Noise ◽  
Packet Delay ◽  
Lms Algorithm ◽  
Least Mean Square ◽  
Delay Jitter ◽  
Lms Filter ◽  
Ip Packet ◽  
Synchronization Accuracy

A certain delay jitter will impact the time synchronization accuracy of PTP system in the IP packet switched network. Look the network delay jitters as independently distributed random noise, and use the Least Mean Square (LMS) filter to filter out the noise, that will help to relieve the delay jitter on the system synchronization accuracy. The simulation results show that, by using the LMS algorithm, the research can increase the synchronization accuracy and decrease the bad impact on master and slave time synchronization of packet delay jitter.

scholarly journals CoSiWiNeT: A Clock Synchronization Algorithm for Wide Area IIoT Network

2021 ◽  
Vol 11 (24) ◽  
pp. 11985
Author(s):  
Rahul Nandkumar Gore ◽  
Elena Lisova ◽  
Johan Åkerberg ◽  
Mats Björkman
Keyword(s):  
Failure Modes ◽  
Time Synchronization ◽  
Clock Synchronization ◽  
Packet Delay ◽  
Wide Area ◽  
Monitoring And Control ◽  
Performance Measurements ◽  
Public And Private ◽  
Hardware Failure ◽  
Delay Variations

Recent advances in the industrial internet of things (IIoT) and cyber–physical systems drive Industry 4.0 and have led to remote monitoring and control applications that require factories to be connected to remote sites over wide area networks (WAN). The adequate performance of remote applications depends on the use of a clock synchronization scheme. Packet delay variations adversely impact the clock synchronization performance. This impact is significant in WAN as it comprises wired and wireless segments belonging to public and private networks, and such heterogeneity results in inconsistent delays. Highly accurate, hardware–based time synchronization solutions, global positioning system (GPS), and precision time protocol (PTP) are not preferred in WAN due to cost, environmental effects, hardware failure modes, and reliability issues. As a software–based network time protocol (NTP) overcomes these challenges but lacks accuracy, the authors propose a software–based clock synchronization method, called CoSiWiNeT, based on the random sample consensus (RANSAC) algorithm that uses an iterative technique to estimate a correct offset from observed noisy data. To evaluate the algorithm’s performance, measurements captured in a WAN deployed within two cities were used in the simulation. The results show that the performance of the new algorithm matches well with NTP and state–of–the–art methods in good network conditions; however, it outperforms them in degrading network scenarios.

DCT-BASED VARIABLE STEP SIZE GRIFFITHS' LMS ALGORITHM FOR RANDOM NOISE CANCELLATION IN ECGs

2012 ◽  
Vol 12 (05) ◽  
pp. 1250025
Author(s):  
VEENA N. HEGDE ◽  
RAVISHANKAR DEEKSHIT ◽  
P. S. SATYANARAYANA
Keyword(s):  
Random Noise ◽  
Noise Cancellation ◽  
Lms Algorithm ◽  
Frequency Resolution ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Low Leakage ◽  
Variable Step ◽  
The Time Domain

This paper presents a new random noise cancellation technique for cancelling muscle artifact effects from ECG using ALE in the transformed domain. For this a transform domain variable step size griffith least mean square (TVGLMS) algorithm is proposed. The technique is based on the adaptation of the gradient of the error surface. The method frees both the step size and the gradient from observation noise and reduces the gradient mis-adjustment error. The sluggishness introduced due to the averaging of the gradient in the time domain is overcome by the transformed domain approach. The proposed algorithm uses a discrete cosine transform (DCT)-based signal decomposition due to its improved frequency resolution compared to a discrete Fourier transform (DFT). Furthermore, as the data used symmetrical, DCT usage results in low leakage (bias and variance). The performance of the proposed method has been tested on ECG signals combined with WGN, extracted from MIT database, and compared with several existing techniques like LMS, NLMS, and VGLMS.

Noise Cancellation in ECG Signals with an Unbiased Adaptive Filter

2011 ◽  
pp. 348-366 ◽  
Author(s):  
Yunfeng Wu ◽  
Rangaraj M. Rangayyan
Keyword(s):  
Adaptive Filter ◽  
Adaptive Filters ◽  
Mean Squared Error ◽  
Random Noise ◽  
Recursive Least Squares ◽  
Ecg Signal ◽  
Least Mean Square ◽  
Ecg Signals ◽  
Lms Filter ◽  
Filtered Noise

The electrocardiographic (ECG) signal is a transthoracic manifestation of the electrical activity of the heart and is widely used in clinical applications. This chapter describes an unbiased linear adaptive filter (ULAF) to attenuate high-frequency random noise present in ECG signals. The ULAF does not contain a bias in its summation unit and the filter coefficients are normalized. During the adaptation process, the normalized coefficients are updated with the steepest-descent algorithm to achieve efficient filtering of noisy ECG signals. A total of 16 ECG signals were tested in the adaptive filtering experiments with the ULAF, the least-mean-square (LMS), and the recursive-least-squares (RLS) adaptive filters. The filtering performance was quantified in terms of the root-mean-squared error (RMSE), normalized correlation coefficient (NCC), and filtered noise entropy (FNE). A template derived from each ECG signal was used as the reference to compute the measures of filtering performance. The results indicated that the ULAF was able to provide noise-free ECG signals with an average RMSE of 0.0287, which was lower than the second-best RMSE obtained with the LMS filter. With respect to waveform fidelity, the ULAF provided the highest average NCC (0.9964) among the three filters studied. In addition, the ULAF effectively removed more noise, measured by FNE, in comparison with the LMS and RLS filters in most of the ECG signals tested. The issues of adaptive filter setting for noise reduction in ECG signals are discussed at the end of this chapter.

Development and Implementation of a Semi-Adaptive H∞ Active Control Algorithm for Duct Noise

1999 ◽  
Vol 121 (1) ◽  
pp. 123-125 ◽  
Author(s):  
M. R. Bai ◽  
H. Lin ◽  
Z. Lin
Keyword(s):  
Control Algorithm ◽  
Random Noise ◽  
Active Noise Control ◽  
Lms Algorithm ◽  
Control Synthesis ◽  
Experimental Investigations ◽  
Least Mean Square ◽  
Active Noise ◽  
Youla Parameterization ◽  
Adaptive Compensator

A hybrid active noise control (ANC) scheme for suppressing duct noise based on the H∞ control synthesis is proposed. The controllers are designed in terms of performance, stability, and robustness using a general framework of the H∞ robust control theory. In addition to the fixed controller, the system is further enhanced by introducing an adaptive compensator based on the least-mean-square (LMS) algorithm. Youla parameterization is employed in designing the adaptive compensator so that the resulting system is stable. Experimental investigations demonstrate that the proposed methods are effective in suppressing broadband random noise in a finite-length duct.

An Unbiased Linear Adaptive Filter with Normalized Coefficients for the Removal of Noise in Electrocardiographic Signals

2009 ◽  
Vol 3 (4) ◽  
pp. 73-90 ◽  
Author(s):  
Yunfeng Wu ◽  
Rangaraj M. Rangayyan
Keyword(s):  
Adaptive Filter ◽  
Adaptive Filters ◽  
Mean Squared Error ◽  
Random Noise ◽  
Recursive Least Squares ◽  
Least Mean Square ◽  
Ecg Signals ◽  
Squared Error ◽  
Lms Filter ◽  
Filtered Noise

The authors propose an unbiased linear adaptive filter (ULAF) to eliminate high-frequency random noise in electrocardiographic (ECG) signals. The ULAF does not contain a bias in its summation unit, and the filter coefficients are normalized. During the adaptation process, the normalized coefficients are updated with the steepest-descent algorithm in order to achieve efficient filtering of noisy ECG signals. The authors tested the ULAF with ECG signals recorded from 16 subjects, and compared the performance of the ULAF with that of the least-mean-square (LMS) and recursive-least-squares (RLS) adaptive filters. The filtering performance was quantified in terms of the root-mean-squared error (RMSE), normalized correlation coefficient (NCC), and filtered noise entropy (FNE). A template derived from each ECG signal was used as the reference to compute the measures of filtering performance. The results indicated that the ULAF was able to provided noise-free ECG signals with an average RMSE of 0.0287, which was lower than the second best RMSE (0.0365) obtained with the LMS filter. With respect to waveform fidelity, the proposed ULAF provided the highest average NCC (0.9964) among the three filters studied. In addition, the ULAF effectively removed more noise measured by FNE versus the LMS and RLS filters in most of the ECG signals tested.

scholarly journals An Effective Adaptive Combination Strategy for Distributed Learning Network

2021 ◽  
Vol 11 (12) ◽  
pp. 5723
Author(s):  
Chundong Xu ◽  
Qinglin Li ◽  
Dongwen Ying
Keyword(s):  
Minimum Variance ◽  
Iteration Scheme ◽  
Estimation Problem ◽  
Lms Algorithm ◽  
Unbiased Estimation ◽  
Mean Square ◽  
Least Mean Square ◽  
Combination Strategy ◽  
Adaptive Combination ◽  
Diffusion Networks

In this paper, we develop a modified adaptive combination strategy for the distributed estimation problem over diffusion networks. We still consider the online adaptive combiners estimation problem from the perspective of minimum variance unbiased estimation. In contrast with the classic adaptive combination strategy which exploits orthogonal projection technology, we formulate a non-constrained mean-square deviation (MSD) cost function by introducing Lagrange multipliers. Based on the Karush–Kuhn–Tucker (KKT) conditions, we derive the fixed-point iteration scheme of adaptive combiners. Illustrative simulations validate the improved transient and steady-state performance of the diffusion least-mean-square LMS algorithm incorporated with the proposed adaptive combination strategy.

scholarly journals Modified GSC Method to Reduce the Distortion of the Enhanced Speech Signal Using Cross-Correlation and Sidelobe Neutralization

2021 ◽  
Vol 11 (14) ◽  
pp. 6288
Author(s):  
Hang Su ◽  
Chang-Myung Lee
Keyword(s):  
Speech Signal ◽  
Output Signal ◽  
Cross Correlation ◽  
Acoustic Noise ◽  
Audio Signal ◽  
Noise Signal ◽  
Lms Algorithm ◽  
Least Mean Square ◽  
Experiment Data ◽  
Noise Component

The generalized sidelobe canceller (GSC) method is a common algorithm to enhance audio signals using a microphone array. Distortion of the enhanced audio signal consists of two parts: the residual acoustic noise and the distortion of the desired audio signal, which means that the desired audio signal is damaged. This paper proposes a modified GSC method to reduce both kinds of distortion when the desired audio signal is a non-stationary speech signal. First, the cross-correlation coefficient between the canceling signal and the error signal of the least mean square (LMS) algorithm was added to the adaptive process of the GSC method to reduce the distortion of the enhanced signal while the energy of the desired signal frame was increased suddenly. The sidelobe pattern of beamforming was then presented to estimate the noise signal in the beamforming output signal of the GSC method. The noise component of the beamforming output signal was decreased by subtracting the estimated noise signal to improve the denoising performance of the GSC method. Finally, the GSC-SN-MCC method was proposed by merging the above two methods. The experiment was performed in an anechoic chamber to validate the proposed method in various SNR conditions. Furthermore, the simulated calculation with inaccurate noise directions was conducted based on the experiment data to inspect the robustness of the proposed method to the error of the estimated noise direction. The experiment data and calculation results indicated that the proposed method could reduce the distortion effectively under various SNR conditions and would not cause more distortion if the estimated noise direction is far from the actual noise direction.

scholarly journals An Efficient Algorithm for Partial Discharge Localization in High-Voltage Systems Using Received Signal Strength

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4000 ◽  
Author(s):  
Umar F. Khan ◽  
Pavlos I. Lazaridis ◽  
Hamd Mohamed ◽  
Ricardo Albarracín ◽  
Zaharias D. Zaharis ◽  
...  
Keyword(s):  
High Voltage ◽  
Time Synchronization ◽  
Clock Synchronization ◽  
Human Life ◽  
Partial Discharge ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Time Of Arrival ◽  
Localization Algorithm ◽  
Require Time

The term partial discharge (PD) refers to a partial bridging of insulating material between electrodes that sustain an electric field in high-voltage (HV) systems. Long-term PD activity can lead to catastrophic failures of HV systems resulting in economic, energy and even human life losses. Such failures and losses can be avoided by continuously monitoring PD activity. Existing techniques used for PD localization including time of arrival (TOA) and time difference of arrival (TDOA), are complicated and expensive because they require time synchronization. In this paper, a novel received signal strength (RSS) based localization algorithm is proposed. The reason that RSS is favoured in this research is that it does not require clock synchronization and it only requires the energy of the received signal rather than the PD pulse itself. A comparison was made between RSS based algorithms including a proposed algorithm, the ratio and search and the least squares algorithm to locate a PD source for nine different positions. The performance of the algorithms was evaluated by using two field scenarios based on seven and eight receiving nodes, respectively. The mean localization error calculated for two-field-trial scenarios show, respectively, 1.80 m and 1.76 m for the proposed algorithm for all nine positions, which is the lowest of the three algorithms.

The Hardware Design of Measurement System of Transmission Lines Based on Wireless Communication

2015 ◽  
Vol 1092-1093 ◽  
pp. 366-369
Author(s):  
Shu Min Sun ◽  
Wen Juan Jiang ◽  
Yu Meng ◽  
Yan Cheng
Keyword(s):  
Wireless Communication ◽  
Data Storage ◽  
Measurement System ◽  
Transmission Lines ◽  
High Speed ◽  
Time Synchronization ◽  
Clock Synchronization ◽  
Report Generation ◽  
Test Efficiency ◽  
Synchronization Module

A set of measurement system for the testing of transmission lines, composing of wireless center station, wireless current acquisition and transmission nodes, wireless voltage acquisition and transmission node, was designed, which was based on wireless communication. The high speed wireless bridge working at 2.4GHz together with the clock synchronization module based on the IEEE1588 communicating protocol were both employed for the communication and time synchronization separately. The measurement system has data storage, waveform display, data analysis, automatic report generation and other functions. The measurement system can greatly reduced arrangement of cables, thereafter improved the test efficiency.

A Multi-Source Dynamic Determination Algorithm for Digital Synchronization Equipment

2014 ◽  
Vol 654 ◽  
pp. 370-373
Author(s):  
Bin Zhang ◽  
Bao Ren Chen ◽  
Yue Zhuo ◽  
Guang Cai Wang ◽  
Yi Jie Ding
Keyword(s):  
Time Synchronization ◽  
Weighted Average ◽  
Reference Source ◽  
Time Frequency ◽  
Output Performance ◽  
Synchronization Signal ◽  
Dynamic Source ◽  
Security And Reliability ◽  
Multiple Reference ◽  
Synchronization Accuracy

In order to improve the security and reliability of digital synchronization network, digital synchronized equipment mostly uses reference source design and ensure the output performance in abnormal situation by redundancy back-up of multiple reference sources. The paper not only describes the concept of time-frequency equipment reference source and its judgment index, but also details a multi-source dynamic determination algorithm for digital synchronization equipment. A multi-component weighted average approach is designed the multi-source dynamic source selected processes by the study of several time sources of anomaly detection to improve the accuracy of the synchronization signal. The algorithm with simple structure can help keeping the high synchronization accuracy of multi-source time synchronization system.

Sign in / Sign up

Export Citation Format

Share Document