scholarly journals A simple faulted phase-based fault distance estimation algorithm for a loop distribution system

2022 ◽  
Vol 25 (1) ◽  
pp. 14
Author(s):  
Shwe Myint ◽  
Warit Wichakool
Keyword(s):  
Traveling Wave ◽  
Distribution System ◽  
Signal To Noise Ratio ◽  
Distance Estimation ◽  
Estimation Algorithm ◽  
Estimation Accuracy ◽  
Discrete Wavelet ◽  
Band Pass Filter ◽  
Localization Algorithm ◽  
Pass Filter

This paper presents a single ended faulted phase-based traveling wave fault localization algorithm for loop distribution grids which is that the sensor can get many reflected signals from the fault point to face the complexity of localization. This localization algorithm uses a band pass filter to remove noise from the corrupted signal. The arriving times of the faulted phase-based filtered signals can be obtained by using phase-modal and discrete wavelet transformations. The estimated fault distance can be calculated using the traveling wave method. The proposed algorithm presents detail level analysis using three detail levels coefficients. The proposed algorithm is tested with MATLAB simulation single line to ground fault in a 10 kV grounded loop distribution system. The simulation result shows that the faulted phase time delay can give better accuracy than using conventional time delays. The proposed algorithm can give fault distance estimation accuracy up to 99.7% with 30 dB contaminated signal-to-noise ratio (SNR) for the nearest lines from the measured terminal.

scholarly journals Artifacts removal from breath sound recordings in pediatric population

2018 ◽  
Vol 154 ◽  
pp. 01046
Author(s):  
Yusuf A Amrulloh ◽  
Jawahir A K Haq
Keyword(s):  
Signal To Noise Ratio ◽  
Pediatric Population ◽  
Breath Sound ◽  
Discrete Wavelet ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Sound Recordings ◽  
Breath Sounds ◽  
Band Pass ◽  
Lower Magnitude

Breath sound recordings from pediatric subjects pose more processing complications. Children, especially the younger ones, are not able to follow instructions to stay calm during recording. This makes their recordings not only contain stationary artifacts but also non-stationary artifacts such as movement of subjects and their heartbeats. Further, the breath sounds from pediatric subjects also have lower magnitude compared to adults. In this work, we proposed to address those problems by developing a method to remove the artifacts from breath sound recordings. We implemented a combination of a Butterworth band pass filter and a discrete wavelet filter. We tested three types of wavelets (Coiflet, Symlet and Daubechies). Ten level decompositions and a set of hard thresholds were implemented in our work. Our results show that our developed method was capable of removing the artifacts significantly while maintaining the signal of interest. The highest signal to noise ratio improvement (10.65dB) was achieved by 32 orders Symlet.

Identification of Brain disorders by Sub-band Decomposition of EEG signals and Measurement of Signal to Noise Ratio

2016 ◽  
Vol 4 (3) ◽  
pp. 568
Author(s):  
Hadaate Ullah ◽  
Shahin Mahmud ◽  
Rubana Hoque Chowdhury
Keyword(s):  
Feature Extraction ◽  
Signal To Noise Ratio ◽  
Automated System ◽  
Discrete Wavelet ◽  
Band Pass Filter ◽  
Eeg Signal ◽  
Brain Disorders ◽  
Signal To Noise ◽  
Pass Filter ◽  
Noise Ratio

<p>In the case of medical science, one of the most restless researches is the identification of abnormalities in brain. Electroencephalogram (EEG) is the main tool for determining the electrical activity of brain and it contains rich information associated to the varieties physiological states of brain. The purpose of this task is to identify the EEG signal as order or disorder. It is proposed to enrich an automated system for the identification of brain disorders. An EEG signal of a patient has been taken as a sample. The simulation has been done by MATLAB. The file which consists of the signal has been called in and plotted the signals in MATLAB. The proposed system covers pre-processing, feature extraction, feature selection and classification. By the pre-processing the noises are ejected. In this case the signal has been filtered using band pass filter. The Discrete Wavelet Transform (DWT) has been used to decompose the EEG signal into Sub-band signal. The feature extraction methods have been used to extract the EEG signal into frequency domain and the time domain features. The SNR (Signal to Noise ratio) is obtained in this work is 1.1281dB.<strong></strong></p>

scholarly journals NOISE STABILITY OF SIGNAL RECEPTION ALGORITHMS WITH MULTIPULSE PULSE-POSITION MODULATION

2018 ◽  
Vol 42 (1) ◽  
pp. 167-174 ◽  
Author(s):  
V. I. Parfenov ◽  
D. Y. Golovanov
Keyword(s):  
Communication Systems ◽  
Pulse Sequence ◽  
Signal To Noise Ratio ◽  
Point Of View ◽  
Estimation Accuracy ◽  
Pulse Position Modulation ◽  
Signal To Noise ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Noise Ratio

An algorithm for estimating time positions and amplitudes of a periodic pulse sequence from a small number of samples was proposed. The number of these samples was determined only by the number of pulses. The performance of this algorithm was considered on the assumption that the spectrum of the original signal is limited with an ideal low-pass filter or the Nyquist filter, and conditions for the conversion from one filter to the other were determined. The efficiency of the proposed algorithm was investigated through analyzing in which way the dispersion of estimates of time positions and amplitudes depends on the signal-to-noise ratio and on the number of pulses in the sequence. It was shown that, from this point of view, the efficiency of the algorithm decreases with increasing number of sequence pulses. Besides, the efficiency of the proposed algorithm decreases with decreasing signal-to-noise ratio.It was found that, unlike the classical maximum likelihood algorithm, the proposed algorithm does not require a search for the maximum of a multivariable function, meanwhile characteristics of the estimates are practically the same for both these methods. Also, it was shown that the estimation accuracy of the proposed algorithm can be increased by an insignificant increase in the number of signal samples.The results obtained may be used in the practical design of laser communication systems, in which the multipulse pulse-position modulation is used for message transmission. 

scholarly journals Continuous Gesture Recognition Based on Time Sequence Fusion Using MIMO Radar Sensor and Deep Learning

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 869 ◽  
Author(s):  
Wentai Lei ◽  
Xinyue Jiang ◽  
Long Xu ◽  
Jiabin Luo ◽  
Mengdi Xu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Gesture Recognition ◽  
Continuous Wave ◽  
Short Term Memory ◽  
Estimation Algorithm ◽  
Intermediate Frequency ◽  
Mimo Radar ◽  
Time Sequence ◽  
Band Pass Filter ◽  
Pass Filter

Gesture recognition that is based on high-resolution radar has progressively developed in human-computer interaction field. In a radar recognition-based system, it is challenging to recognize various gesture types because of the lacking of gesture transversal feature. In this paper, we propose an integrated gesture recognition system that is based on frequency modulated continuous wave MIMO radar combined with deep learning network for gesture recognition. First, a pre-processing algorithm, which consists of the windowed fast Fourier transform and the intermediate-frequency signal band-pass-filter (IF-BPF), is applied to obtain improved Range Doppler Map. A range FFT based MUSIC (RFBM) two-dimensional (2D) joint super-resolution estimation algorithm is proposed to obtain a Range Azimuth Map to obtain gesture transversal feature. Range Doppler Map and Range Azimuth Map then respectively form a Range Doppler Map Time Sequence (RDMTS) and a Range Azimuth Map Time Sequence (RAMTS) in gesture recording duration. Finally, a Dual stream three-dimensional (3D) Convolution Neural Network combined with Long Short Term Memory (DS-3DCNN-LSTM) network is designed to extract and fuse features from both RDMTS and RAMTS, and then classify gestures with radial and transversal change. The experimental results show that the proposed system could distinguish 10 types of gestures containing transversal and radial motions with an average accuracy of 97.66%.

A 1D time-varying median filter for seismic random, spike-like noise elimination

Geophysics ◽  
2009 ◽  
Vol 74 (1) ◽  
pp. V17-V24 ◽  
Author(s):  
Yang Liu ◽  
Cai Liu ◽  
Dian Wang
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Random Noise ◽  
Threshold Value ◽  
Band Pass Filter ◽  
Time Varying ◽  
Noise Elimination ◽  
Pass Filter ◽  
Median Filters

Random noise in seismic data affects the signal-to-noise ratio, obscures details, and complicates identification of useful information. We have developed a new method for reducing random, spike-like noise in seismic data. The method is based on a 1D stationary median filter (MF) — the 1D time-varying median filter (TVMF). We design a threshold value that controls the filter window according to characteristics of signal and random, spike-like noise. In view of the relationship between seismic data and the threshold value, we chose median filters with different time-varying filter windows to eliminate random, spike-like noise. When comparing our method with other common methods, e.g., the band-pass filter and stationary MF, we found that the TVMF strikes a balance between eliminating random noise and protecting useful information. We tested the feasibility of our method in reducing seismic random, spike-like noise, on a synthetic dataset. Results of applying the method to seismic land data from Texas demonstrated that the TVMF method is effective in practice.

scholarly journals ACE-PI: PAPR Reduction in OFDM Systems Using Constellation Extension with Peak Insertion

2019 ◽  
Vol 8 (11) ◽  
pp. 229-233
Keyword(s):  
Bit Error Rate ◽  
Signal To Noise Ratio ◽  
Papr Reduction ◽  
Band Pass Filter ◽  
Ofdm Systems ◽  
Effective Technique ◽  
Pass Filter ◽  
Reduction Techniques ◽  
Band Pass ◽  
Clipping Technique

In this study, a proposal is offered in order to calculate the Bit Error Rate with the Signal to Noise Ratio. Here in this paper, it is illustrated that by comparing this analysis among the other mechanisms effective results can be obtained. By applying the ACE scheme in which the clipping technique block is replaced with Peak Inversion (PI) and butter worth band-pass filter is added after the ACE constraint block for generating less distortion and more smoothing. As, it has been concluded from a survey that among different PAPR reduction techniques, PI found to be an effective technique which can reduce PAPR to an extent by incorporating a relatively high impulse. The MATLAB is used for analyzing the enhanced ACE scheme that offers better results in terms of both PAPR and BER.

scholarly journals Optimised Design and Implementation of Band-Pass Filter for Neural Recording System

2020 ◽  
Vol 8 (5) ◽  
pp. 1821-1826
Keyword(s):  
Power Consumption ◽  
Filter Design ◽  
Signal To Noise Ratio ◽  
Infinite Impulse Response ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Significant Saving ◽  
Iir Filter ◽  
Band Pass ◽  
Neural Recording System

In this paper, an eight order efficient digital infinite impulse response filter is designed to improve the signal to noise ratio (SNR) and minimise the hardware and power consumption. For this task, an optimisation method has been adapted to reduce the root mean square error and hardware usage. The filter has been designed and analysed using Matlab and Modelsim, the implementation has been synthesis on Xilinx Spartan 3E-100 (xc3s100e) field-programmable gate array board. Moreover, an optimisation process using parallel algorithm has bee adapted for further reduction in the hardware area and power consumption. The results show the Band Pass Filter effectively functions in real time recording application with significant improvement in the SNR which could achieve high-velocity selective resolution. The present work offers a structure of implementing a band-pass filter on FPGAs using a nonlinear digital filter shows a significant saving of 25.4% in power consumption and 29.9% of the hardware size comparing with the latest algorithm of IIR filter design. Consequently, this is an essential development to enhance the neural signals to be adopted as reference or control signals in artificial limbs devices.

scholarly journals QIM - Based Audio Watermarking with Combination Technique of DCT-QR-CPT

2019 ◽  
Vol 7 (1) ◽  
pp. 112 ◽  
Author(s):  
RENDY DWI RENDRAGRAHA ◽  
GELAR BUDIMAN ◽  
IRMA SAFITRI
Keyword(s):  
Signal To Noise Ratio ◽  
Audio Watermarking ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Opinion Score ◽  
Low Pass ◽  
Band Pass ◽  
Speed Change ◽  
Index Modulation

ABSTRAKAudio watermarking adalah teknik memasukkan informasi ke dalam file audio dan untuk melindungi hak cipta data digital dari distribusi ilegal. Makalah ini memperkenalkan audio stereo watermarking berdasarkan Quantization Index Modulation (QIM) dengan teknik gabungan Discrete Cosine Transform (DCT) - QRCartesian Polar Transform (CPT). Host audio dibagi menjadi beberapa frame, selanjutnya setiap frame ditransformasi oleh DCT, kemudian output DCT diuraikan menjadi matriks orthogonal dan matriks segitiga menggunakan metode QR. Selanjutnya, CPT mengubah dua koefisien kartesian dari matriks segitiga (R) pada posisi (1,1) dan (2,2) menjadi koefisien polar. Setelah itu, penyisipan dilakukan pada koefisien polar oleh QIM. Hasil simulasi menunjukkan bahwa imperseptibilitas audio terwatermark berkualitas baik dengan Signal to Noise Ratio (SNR)> 20, Mean Opinion Score (MOS)> 4 dan tahan terhadap serangan seperti Low Pass Filter (LPF) dan Band Pass Filter (BPF) dengan cut off 25-6k, resampling, Linear Speed Change (LSC) dan MP3 Compression dengan rate diatas 64 kbps.Kata kunci: Audio Watermarking, CPT, DCT, QIM, QR ABSTRACTAudio watermarking is a technique for inserting information into an audio file and to protect the copyright of digital data from illegal distribution. This paper introduces a stereo audio watermarking based on Quantization Index Modulation (QIM) with combined technique Discrete Cosine Transform (DCT) – QR – Cartesian Polar Transform (CPT). Each frame of a host audio is transformed by DCT, then DCT output is decomposed using QR method. Next, CPT transform two cartesian coefficients from triangular matrix (R) in position (1,1) and (2,2) to polar coefficients. After that, embedding is executed on polar coefficients by QIM. The simulation result shows that the imperceptibility is good with Signal to Noise Ratio (SNR)>20, Mean Opinion Score (MOS)>4 and it is robust against attacks such as Low Pass Filter (LPF) and Band Pass Filter (BPF) with cut off 25-6k, Resampling, Linear Speed Change and MP3 Compression with rate 64 kbps and above. Keywords: Audio Watermarking, CPT, DCT, QIM, QR

A novel variable filter band discrete wavelet transform: Theory and principle

2014 ◽  
Vol 12 (04) ◽  
pp. 1460006
Author(s):  
Zhong Zhang ◽  
Hiroshi Toda ◽  
Takashi Imamura ◽  
Tetsuo Miyake
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Perfect Reconstruction ◽  
Discrete Wavelet ◽  
Band Pass Filter ◽  
Mother Wavelet ◽  
Pass Filter ◽  
Signal Characteristics ◽  
Filter Characteristic ◽  
Band Pass

It is well-known that a mother wavelet for the discrete wavelet transform (DWT) has the band-pass filter characteristic with octave width in the frequency domain and can be used for octave analysis. However, it is possible that the octave analysis is not necessarily the most suitable to match the analysis signal. In this study, in order to construct the most suitable basis to match the analysis signal, a novel variable-filter band discrete wavelet transform (VFB-DWT) is proposed. It is achieved by using variable-band filters instead of conventional decomposition and reconstruction sequences, which are designed in consideration of the real signal characteristics. Additionally, it is proven that perfect reconstruction of the analysis signal by VFB-DWT is guaranteed using the perfect shift invariant theorem that underlies the theory of the PTI-CDWT having base DWT.

scholarly journals A Phase Fluctuation Based Practical Quantum Random Number Generator Scheme with Delay-Free Structure

2020 ◽  
Vol 10 (7) ◽  
pp. 2431 ◽  
Author(s):  
Min Huang ◽  
Ziyang Chen ◽  
Yichen Zhang ◽  
Hong Guo
Keyword(s):  
Phase Noise ◽  
Distribution System ◽  
Random Number ◽  
Quantum Noise ◽  
Laser Diodes ◽  
Phase Fluctuation ◽  
Random Number Generation ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Number Generation

Quantum random number generators are widely used in many applications, ranging from sampling and simulation, fundamental science to cryptography, such as a quantum key distribution system. Among all the previous works, quantum noise from phase fluctuation of laser diodes is one of the most commonly used random source in the quantum random number generation, and many practical schemes based on phase noise with compact systems have been proposed so far. Here, we proposed a new structure of phase noise scheme, utilizing the phase fluctuation from two laser diodes with a slight difference of center wavelength. By analyzing the frequency components and adopting an appropriate band-pass filter, we prove that our scheme extracts quantum noise and filtered other classical noises substantially. Results of a randomness test shows that the extracted random sequences are of good performance. Due to lack of delay-line and the low requirement on other devices in this system, our scheme is promising in future scenarios for miniaturized quantum random number generation systems.

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