Stellar Image Location with Maximum Correlation Procedure

1995 ◽  
pp. 363-363
Author(s):  
Zhu Zi
Keyword(s):  
Maximum Correlation ◽  
Correlation Procedure ◽  
Stellar Image

scholarly journals Stellar Image Location with Maximum Correlation Procedure

1995 ◽  
Vol 166 ◽  
pp. 363-363
Author(s):  
Zhu Zi
Keyword(s):  
Observational Data ◽  
Estimation Method ◽  
Positional Accuracy ◽  
Maximum Correlation ◽  
Single Star ◽  
Mathematical Performance ◽  
Location Methods ◽  
Photoelectric Technique ◽  
Correlation Procedure ◽  
Stellar Image

The location method and accuracy analysis has become a very important subject in astrometry since the photoelectric technique was widely applied. The location methods of the stellar images observed with the slit micrometer are discussed in this paper, and a new estimation method called the maximum correlation procedure is presented. This procedure has already been used to process and analyze the observational data. Because of the ideal mathematical performance of the correlation function, the procedure provides us a good way to determine image locations. By means of simulated observations according to the theoretical analysis, we find that the locating accuracy and the limiting magnitude for this method is much higher than those of traditional locating method. For the observational data of about one thousand stars obtained with the Photoelectric Astrolabe at Yunnan Astronomical Observatory, the positional accuracy of a single star using the maximum correlation is improved by 0.045 arcsec over that with the median. The maximum correlation procedure has also increased the data reduction ability for faint star observations with very low signal to noise ratios.

Description and validation of an ECG removal procedure for EMGdi power spectrum analysis

1986 ◽  
Vol 60 (3) ◽  
pp. 1073-1081 ◽  
Author(s):  
S. Levine ◽  
J. Gillen ◽  
P. Weiser ◽  
M. Gillen ◽  
E. Kwatny
Keyword(s):  
Cross Correlation ◽  
Regression Coefficients ◽  
Total Power ◽  
Median Frequency ◽  
Maximum Correlation ◽  
Power Spectral ◽  
Centroid Frequency ◽  
Electrocardiogram Ecg ◽  
Correlation Procedure ◽  
Power Standard

We describe a cross-correlation procedure for removing contaminating electrocardiogram (ECG) complexes from the diaphragmatic electromyogram (EMGdi). First, the operator selects ECG templates from the EMGdi signal during expiratory intervals. Second, these templates are used to locate ECG complexes occurring during inspiratory EMGdi activity. Third, at the point of maximum correlation between the template and these ECG complexes, the template is adjusted in size and offset to “match” the ECG complex, and adjustments are determined by the linear regression coefficients. Finally, the modified template is subtracted from the EMGdi signal. To evaluate our method, we compared the power spectral density (PSD) obtained from processing EMGdi signals by our method with those obtained from the EMGdi signal in which ECG complexes had been removed by gating. Our results indicate that PSD obtained by these two different methods shows no statistically significant differences with respect to the following features: centroid frequency, median frequency, total power, standard deviation, skewness, and kurtosis.

COMPOUND FAULT DIAGNOSIS OF BEARINGS USING AN IMPROVED SPECTRAL KURTOSIS BY MAXIMUM CORRELATION KURTOSIS DECONVOLUTION (MCKD).

2020 ◽  
Vol 9 (8) ◽  
pp. 66-72
Keyword(s):  
Fault Diagnosis ◽  
Resonance Frequency ◽  
Background Noise ◽  
Maximum Correlation ◽  
Vibration Signals ◽  
Filter Length ◽  
Frequency Bands ◽  
Noise Interference ◽  
Spectral Kurtosis

This paper discusses the use of Maximum Correlation kurtosis deconvolution (MCKD) method as a pre-processor in fast spectral kurtosis (FSK) method in order to find the compound fault characteristics of the bearing, by enhancing the vibration signals. FSK only extracts the resonance bands which have maximum kurtosis value, but sometimes it might possible that faults occur in the resonance bands which has low kurtosis value, also the faulty signals missed due to noise interference. In order to overcome these limitations FSK used with MCKD, MCKD extracts various faults present in different resonance frequency bands; also detect the weak impact component, as MCKD also dealt with strong background noise. By obtaining the MCKD parameters like, filter length & deconvolution period, we can extract the compound fault feature characteristics.

scholarly journals Environmental Performance Index: Regional Aspect

2018 ◽  
Vol 41 ◽  
pp. 02003
Author(s):  
Sergey Bereznev ◽  
Olga Zonova ◽  
Evdokiya Kulpina
Keyword(s):  
Performance Index ◽  
Environmental Performance ◽  
Efficiency Index ◽  
Environmental Indicators ◽  
Regional Level ◽  
Environmental Efficiency ◽  
Maximum Correlation ◽  
National System ◽  
Environmental Performance Index ◽  
Regional Aspect

The methodology of calculation of environmental performance index is considered in the article. The necessity of assessing the environmental efficiency index at the regional level in connection with which the authors attempted to adapt the indicators is proved; the recommendations on improving the national system of environmental indicators for the purpose of maximum correlation with the indicators of the environmental performance index are given.

scholarly journals Clustering Irregular Shapes Using High-Order Neurons

2000 ◽  
Vol 12 (10) ◽  
pp. 2331-2353 ◽  
Author(s):  
H. Lipson ◽  
H. T. Siegelmann
Keyword(s):  
Synaptic Weight ◽  
Hebbian Learning ◽  
Second Order ◽  
High Order ◽  
Maximum Correlation ◽  
Overlapping Clusters ◽  
Homogeneous Coordinates ◽  
Irregular Shapes ◽  
Data Clusters ◽  
Iris Data

This article introduces a method for clustering irregularly shaped data arrangements using high-order neurons. Complex analytical shapes are modeled by replacing the classic synaptic weight of the neuron by high-order tensors in homogeneous coordinates. In the first- and second-order cases, this neuron corresponds to a classic neuron and to an ellipsoidal-metric neuron. We show how high-order shapes can be formulated to follow the maximum-correlation activation principle and permit simple local Hebbian learning. We also demonstrate decomposition of spatial arrangements of data clusters, including very close and partially overlapping clusters, which are difficult to distinguish using classic neurons. Superior results are obtained for the Iris data.

scholarly journals TRACE OF PHASE-SPACE NONCOMMUTATIVITY IN RESPONSE OF A FREE PARTICLE TO LINEARIZED GRAVITATIONAL WAVES

2013 ◽  
Vol 28 (35) ◽  
pp. 1350161 ◽  
Author(s):  
SUNANDAN GANGOPADHYAY ◽  
ANIRBAN SAHA ◽  
SWARUP SAHA
Keyword(s):  
Phase Space ◽  
Gravitational Waves ◽  
Cross Correlation ◽  
Free Particle ◽  
Momentum Scale ◽  
Specific Frequency ◽  
Global Nature ◽  
Space Noncommutativity ◽  
Correlation Procedure ◽  
Noncommutative Parameter

Interaction of linearized gravitational waves with a otherwise free particle has been studied quantum mechanically in a noncommutative (NC) phase-space to examine whether the particle's response to the gravitational wave gets modified due to spatial and/or momentum noncommutativity. The result shows that momentum noncommutativity introduces a oscillatory noise with a specific frequency determined by the fundamental momentum scale and particle mass. Because of the global nature of the phase-space noncommutativity such noise will have similar characteristics for all detector sites and thus will stand out in a data cross-correlation procedure. If detected, this noise will provide evidence of momentum noncommutativity and also an estimation of the relevant noncommutative parameter.

Study on Auto-Search Algorithm Based on Subsection Correlation for Loran-C

2012 ◽  
Vol 241-244 ◽  
pp. 1751-1755
Author(s):  
Yin Bing Zhu ◽  
Ke Jing Cao ◽  
Bao Li
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Arrival Time ◽  
Search Algorithm ◽  
Digital Signal ◽  
Digital Processing ◽  
Digital Receiver ◽  
Maximum Correlation ◽  
Key Steps ◽  
Signal Search

Auto-search is one of the key steps in digital signal processing for Loran-C receivers, however, for digital sampling Loran-C signal, the principle search algorithm is unable to realize signal search veraciously because of the asynchronism between sampling clock and transmitting station clock. For this question, an auto-search algorithm based on subsection correlation for Loran-C is presented after analyzing the principle search algorithm. The experiment results show that for the received digital Loran-C signal, there are several correlation and accumulation values of master and secondary stations to exceed the search thresholds; the maximum correlation and accumulation value of the presented algorithm is far higher than that of the principle algorithm. That is to say, the presented algorithm can search the arrival time of master and secondary station successfully, solve the problem of clock asynchronism effectively, and enhance the search sensitivity of the receiver, which have great significance for digital processing of Loran-C signal and the engineering realization of Loran-C digital receiver.

Sign in / Sign up

Export Citation Format

Share Document