Hilbert transform based simple detection and indice analyze of voltage sags using synthetic data

2017 ◽  
Author(s):  
Ferhat Ucar ◽  
Omer Faruk Alcin ◽  
Besir Dandil ◽  
Fikret Ata
Keyword(s):  
Hilbert Transform ◽  
Synthetic Data ◽  
Voltage Sags ◽  
Simple Detection

scholarly journals Real-time estimation of phase and amplitude with application to neural data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael Rosenblum ◽  
Arkady Pikovsky ◽  
Andrea A. Kühn ◽  
Johannes L. Busch
Keyword(s):  
Real Time ◽  
Hilbert Transform ◽  
Brain Activity ◽  
Synthetic Data ◽  
Time Estimation ◽  
Beta Band ◽  
Data Set ◽  
Real Time Estimation ◽  
The Hilbert Transform ◽  
Physical Phenomena

AbstractComputation of the instantaneous phase and amplitude via the Hilbert Transform is a powerful tool of data analysis. This approach finds many applications in various science and engineering branches but is not proper for causal estimation because it requires knowledge of the signal’s past and future. However, several problems require real-time estimation of phase and amplitude; an illustrative example is phase-locked or amplitude-dependent stimulation in neuroscience. In this paper, we discuss and compare three causal algorithms that do not rely on the Hilbert Transform but exploit well-known physical phenomena, the synchronization and the resonance. After testing the algorithms on a synthetic data set, we illustrate their performance computing phase and amplitude for the accelerometer tremor measurements and a Parkinsonian patient’s beta-band brain activity.

Response and Reinforcement in Operant Audiometry

1987 ◽  
Vol 52 (3) ◽  
pp. 294-299 ◽  
Author(s):  
Michael A. Primus
Keyword(s):  
Operant Conditioning ◽  
Space Versus ◽  
Visual Space ◽  
Central Processing ◽  
Operant Discrimination ◽  
Conditioning Rate ◽  
Significant Difference ◽  
Simple Detection ◽  
Variable Success ◽  
Response Task

Variable success in audiometric assessment of young children with operant conditioning indicates the need for systematic examination of commonly employed techniques. The current study investigated response and reinforcement features of two operant discrimination paradigms with normal I7-month-old children. Findings indicated more responses prior to the onset of habituation when the response task was based on complex central processing skills (localization and coordination of auditory/visual space) versus simple detection. Use of animation in toy reinforcers resulted in more than a twofold increase in the number of subject responses. Results showed no significant difference in response conditioning rate or consistency for the response tasks and forms of reinforcement examined.

Model of multicomponent narrow-band periodical non-stationary random signal

2020 ◽  
Vol 2020 (48) ◽  
pp. 17-24
Author(s):  
I.M. Javorskyj ◽  
◽  
R.M. Yuzefovych ◽  
P.R. Kurapov ◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Real Time ◽  
Hilbert Transform ◽  
Spectral Properties ◽  
Narrow Band ◽  
Analytic Signal ◽  
Random Signal ◽  
Hilbert Transformation ◽  
The Hilbert Transform

The correlation and spectral properties of a multicomponent narrowband periodical non-stationary random signal (PNRS) and its Hilbert transformation are considered. It is shown that multicomponent narrowband PNRS differ from the monocomponent signal. This difference is caused by correlation of the quadratures for the different carrier harmonics. Such features of the analytic signal must be taken into account when we use the Hilbert transform for the analysis of real time series.

Impacts of Voltage Sags and Protection Coordination on Sensitive Equipment in Distribution Systems

2010 ◽  
Vol 130 (6) ◽  
pp. 551-558 ◽  
Author(s):  
Le Viet Tien ◽  
Thavatchai Tayjasanant ◽  
Akihiko Yokoyama ◽  
Bundhit Eua-Arporn
Keyword(s):  
Distribution Systems ◽  
Voltage Sags

A Bayesian View on the Hilbert Transform and the Kramers-Kronig Transform of Electrochemical Impedance Data: Probabilistic Estimates and Quality Scores

2020 ◽  
Author(s):  
Jiapeng Liu ◽  
Ting Hei Wan ◽  
Francesco Ciucci
Keyword(s):  
Power Generation ◽  
Electrochemical Impedance Spectroscopy ◽  
Hilbert Transform ◽  
Electrochemical Impedance ◽  
The Self ◽  
Impedance Data ◽  
The Hilbert Transform ◽  
Validation Tests ◽  
Self Consistency ◽  
Mathematical Relations

<p>Electrochemical impedance spectroscopy (EIS) is one of the most widely used experimental tools in electrochemistry and has applications ranging from energy storage and power generation to medicine. Considering the broad applicability of the EIS technique, it is critical to validate the EIS data against the Hilbert transform (HT) or, equivalently, the Kramers–Kronig relations. These mathematical relations allow one to assess the self-consistency of obtained spectra. However, the use of validation tests is still uncommon. In the present article, we aim at bridging this gap by reformulating the HT under a Bayesian framework. In particular, we developed the Bayesian Hilbert transform (BHT) method that interprets the HT probabilistic. Leveraging the BHT, we proposed several scores that provide quick metrics for the evaluation of the EIS data quality.<br></p>

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

A Technique to Determine Unsteady-State Inhibition Kinetics in the Activated Sludge Process

1989 ◽  
Vol 21 (6-7) ◽  
pp. 593-602 ◽  
Author(s):  
Andrew T. Watkin ◽  
W. Wesley Eckenfelder
Keyword(s):  
Activated Sludge ◽  
Kinetic Parameters ◽  
Curve Fitting ◽  
Glucose Utilization ◽  
Batch Reactor ◽  
Synthetic Data ◽  
Utilization Rate ◽  
Fitting Algorithm ◽  
Test Reactor ◽  
Two Parameter

A technique for rapidly determining Monod and inhibition kinetic parameters in activated sludge is evaluated. The method studied is known as the fed-batch reactor technique and requires approximately three hours to complete. The technique allows for a gradual build-up of substrate in the test reactor by introducing the substrate at a feed rate greater than the maximum substrate utilization rate. Both inhibitory and non-inhibitory substrate responses are modeled using a nonlinear numerical curve-fitting technique. The responses of both glucose and 2,4-dichlorophenol (DCP) are studied using activated sludges with various acclimation histories. Statistically different inhibition constants, KI, for DCP inhibition of glucose utilization were found for the various sludges studied. The curve-fitting algorithm was verified in its ability to accurately retrieve two kinetic parameters from synthetic data generated by superimposing normally distributed random error onto the two parameter numerical solution generated by the algorithm.

Sign in / Sign up

Export Citation Format

Share Document