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.

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.

scholarly journals Noise Reduction from L-Band ALOSPALSAR Data Set Using Spatial Domain Gaussian Low-Pass Filter

2021 ◽  
Vol 3 (Special Issue ICOST 2S) ◽  
pp. 87-93
Author(s):  
Atiya Irfan Shaikh ◽  
Sayyad Shafiyoddin Badroddin
Keyword(s):  
Noise Reduction ◽  
Spatial Domain ◽  
Data Set ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
L Band

A quantum edge detection algorithm for quantum multi-wavelength images

2021 ◽  
pp. 2150017
Author(s):  
Engin Şahin ◽  
İhsan Yilmaz
Keyword(s):  
Edge Detection ◽  
Noise Reduction ◽  
Circuit Complexity ◽  
Detection Algorithm ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Edge Detection Algorithm ◽  
Detection Algorithms ◽  
Low Pass ◽  
Multi Wavelength

Quantum edge detection is one of the important part of quantum image processing. In this paper, a quantum edge detection algorithm is designed for the quantum representation of multi-wavelength image (QRMW) model. The algorithm includes all stages of filtering, enhancement and detection. The proposed algorithm is also designed to apply any filtering operation to QRMW images, not only for a particular filtering operation. The proposed algorithm aims to solve the problems that quantum edge detection algorithms in the literature have processing only for a particular operator and noise reduction. Moreover, the algorithm aims to perform operations more efficiently by using less resources. Low-pass filter (LPF) smoothing operators are applied in the filtering stage for the noise reduction problem. In order to apply all filtering operations to the image, arithmetic operators that can operate with all signed integers are used in the algorithm. The operators Sobel, Prewitt and Scharr in the enhancement stage and the gradient method in the detection stage are used for both verification of the proposed algorithm and comparisons with the existing algorithms. A method with quantitative outcomes is shown to evaluate the performance of the edge detection algorithms. Analysis of the simulations performed on sample images with different operators. The circuit complexity of the algorithm is presented and the comparisons are made with the existing studies. The superiority of the proposed algorithm and its flexibility to be used in other studies are clearly demonstrated by analysis.

scholarly journals Does precipitation pattern foretell climatic shift over Punjab state ?

MAUSAM ◽  
2022 ◽  
Vol 46 (3) ◽  
pp. 325-332
Author(s):  
BHUKAN LAL ◽  
B. LAKSHMANASWAMY
Keyword(s):  
Spectral Analysis ◽  
Kendall Test ◽  
Rainfall Series ◽  
Precipitation Pattern ◽  
Winter Rainfall ◽  
Linear Type ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Climate Shift ◽  
Low Pass

ABSTRACT. Statistical analysis of 82-years (1901-1982) record of precipitation from 27 rain-recording stations in Punjab state of lndia has been carried out to assess the climate shift if any in the state. The central part of the study is the trend and spectrum analysis of annual. monsoon and winter rainfall of different stations in the region. It is seen that frequency distribution of 19 rainfall series out of 81 series is normally distributed. Maikov linear type of persistence is observed in some of the rainfall series. Marin-Kendall test indicates the decreasing trend in winter rainfall of all the stations and is found to be significant in case of Amritsar, Taran Taran, Tanda, Ludhiana and Ranike. Low-pass filter reveals that trend is not linear but oscillatory consisting of periods of 10 years or more. It is seen that winter rainfall of most of the stations exhibits the decreasing trend from 1935-40 to 1965-70. It is also revealed by the low-pass filter curves that winter rainfall of all t1le sla1ions remained below average from 1960 till the end of the study period. The spectral analysis indicates a significant cycle of 4.1 to 27 years in some of the stations and Quasi-Biennial Oscillations (QBO) over many stations.  

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