Q estimation by a match-filter method

2012 ◽  
Author(s):  
Peng Cheng ◽  
Gary F. Margrave
Keyword(s):  
Filter Method ◽  
Match Filter

scholarly journals A Time-Domain Hybrid Analysis Method for Detecting and Quantifying T-Wave Alternans

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xiangkui Wan ◽  
Kanghui Yan ◽  
Linlin Zhang ◽  
Yanjun Zeng
Keyword(s):  
Time Domain ◽  
Correlation Method ◽  
Filter Method ◽  
Least Squares Regression ◽  
Analysis Method ◽  
Hybrid Analysis ◽  
Match Filter ◽  
T Wave ◽  
Increased Risk ◽  
T Wave Alternans

T-wave alternans (TWA) in surface electrocardiograph (ECG) signals has been recognized as a marker of cardiac electrical instability and is hypothesized to be associated with increased risk for ventricular arrhythmias among patients. A novel time-domain TWA hybrid analysis method (HAM) utilizing the correlation method and least squares regression technique is described in this paper. Simulated ECGs containing artificial TWA (cases of absence of TWA and presence of stationary or time-varying or phase-reversal TWA) under different baseline wanderings are used to test the method, and the results show that HAM has a better ability of quantifying TWA amplitude compared with the correlation method (CM) and adapting match filter method (AMFM). The HAM is subsequently used to analyze the clinical ECGs, and results produced by the HAM have, in general, demonstrated consistency with those produced by the CM and the AMFM, while the quantifying TWA amplitudes by the HAM are universally higher than those by the other two methods.

A match-filter method for measuring group velocity and attenuation in the laboratory

2020 ◽  
Author(s):  
Li Min* ◽  
Tang Genyang ◽  
Zhao Liming ◽  
He Yanxiao ◽  
Dong Chunhui ◽  
...  
Keyword(s):  
Group Velocity ◽  
Filter Method ◽  
Match Filter

Enhancing the Performance of One Dimensional Median Filter

2019 ◽  
Vol 118 (7) ◽  
pp. 73-76
Author(s):  
Sharanabasappa ◽  
P Ravibabu
Keyword(s):  
Impulse Noise ◽  
Rank Order ◽  
Median Filter ◽  
Filter Method ◽  
Salt And Pepper Noise ◽  
Edge Preservation ◽  
Word Level ◽  
Look Ahead ◽  
Filter Architecture ◽  
Salt And Pepper

Nowadays, during the process of Image acquisition and transmission, image information data can be corrupted by impulse noise. That noise is classified as salt and pepper noise and random impulse noise depending on the noise values. A median filter is widely used digital nonlinear filter  in edge preservation, removing of impulse noise and smoothing of signals. Median filter is the widely used to remove salt and pepper noise than rank order filter, morphological filter, and unsharp masking filter. The median filter replaces a sample with the middle value among all the samples present inside the sample window. A median filter will be of two types depending on the number of samples processed at the same cycle i.e, bit level architecture and word level architecture.. In this paper, Carry Look-ahead Adder median filter method will be introduced to improve the hardware resources used in median filter architecture for 5 window and 9 window for 8 bit and 16 bit median filter architecture.

Improvement of the Zeta-Plus Filter Method for Concentration of Viruses from Water

1991 ◽  
Vol 24 (2) ◽  
pp. 217-220 ◽  
Author(s):  
Kazuyoshi Yano ◽  
Yasuko Yoshida ◽  
Mitsumi Kaneko
Keyword(s):  
Filter Method

The Effectiveness of the Fused Weighted Filter Feature Selection Method to Improve Software Fault Prediction

2016 ◽  
Vol 8 ◽  
pp. 5 ◽  
Author(s):  
Fatemeh Alighardashi ◽  
Mohammad Ali Zare Chahooki
Keyword(s):  
Feature Selection ◽  
Feature Selection Method ◽  
Selection Method ◽  
Machine Learning Algorithms ◽  
Fault Prediction ◽  
Filter Method ◽  
Selection Methods ◽  
Software Projects ◽  
Software Fault Prediction ◽  
Software Fault

Improving the software product quality before releasing by periodic tests is one of the most expensive activities in software projects. Due to limited resources to modules test in software projects, it is important to identify fault-prone modules and use the test sources for fault prediction in these modules. Software fault predictors based on machine learning algorithms, are effective tools for identifying fault-prone modules. Extensive studies are being done in this field to find the connection between features of software modules, and their fault-prone. Some of features in predictive algorithms are ineffective and reduce the accuracy of prediction process. So, feature selection methods to increase performance of prediction models in fault-prone modules are widely used. In this study, we proposed a feature selection method for effective selection of features, by using combination of filter feature selection methods. In the proposed filter method, the combination of several filter feature selection methods presented as fused weighed filter method. Then, the proposed method caused convergence rate of feature selection as well as the accuracy improvement. The obtained results on NASA and PROMISE with ten datasets, indicates the effectiveness of proposed method in improvement of accuracy and convergence of software fault prediction.

scholarly journals Optimizing Transmit Sequence and Instrumental Variables Receiver for Dual-Function Complexity System

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yu Yao ◽  
Junhui Zhao ◽  
Lenan Wu
Keyword(s):  
Approximate Solution ◽  
Instrumental Variables ◽  
Performance Index ◽  
Dual Function ◽  
Np Hard ◽  
Match Filter ◽  
Filter Output ◽  
Phase Code ◽  
Discrete Phase ◽  
Simulation Results

This correspondence deals with the joint cognitive design of transmit coded sequences and instrumental variables (IV) receive filter to enhance the performance of a dual-function radar-communication (DFRC) system in the presence of clutter disturbance. The IV receiver can reject clutter more efficiently than the match filter. The signal-to-clutter-and-noise ratio (SCNR) of the IV filter output is viewed as the performance index of the complexity system. We focus on phase only sequences, sharing both a continuous and a discrete phase code and develop optimization algorithms to achieve reasonable pairs of transmit coded sequences and IV receiver that fine approximate the behavior of the optimum SCNR. All iterations involve the solution of NP-hard quadratic fractional problems. The relaxation plus randomization technique is used to find an approximate solution. The complexity, corresponding to the operation of the proposed algorithms, depends on the number of acceptable iterations along with on and the complexity involved in all iterations. Simulation results are offered to evaluate the performance generated by the proposed scheme.

scholarly journals Performance evaluation of GPS / BDS combined single-point positioning based on RTKLIB

2020 ◽  
Vol 165 ◽  
pp. 03009
Author(s):  
Li Yan-yi ◽  
Huang Jin ◽  
Tang Ming-xiu
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Single Point ◽  
Least Square Method ◽  
Least Square ◽  
Filter Method ◽  
Single System ◽  
Positioning Error ◽  
Dual Mode ◽  
Kalman Filter Method

In order to evaluate the performance of GPS / BDS, RTKLIB, an open-source software of GNSS, is used in this paper. In this paper, the least square method, the weighted least square method and the extended Kalman filter method are respectively applied to BDS / GPS single system for data solution. Then, the BDS system and GPS system are used for fusion positioning and the positioning results of the two systems are compared with that of the single system. Through the comparison of experiments, on the premise of using the extended Kalman filter method for positioning, when the GPS signal is not good, BDS data is introduced for dual-mode positioning, the positioning error in e direction is reduced by 36.97%, the positioning error in U direction is reduced by 22.95%, and the spatial positioning error is reduced by 16.01%, which further reflects the advantages of dual-mode positioning in improving a system robustness and reducing the error.

Sign in / Sign up

Export Citation Format

Share Document