scholarly journals PREDICTION OF PROBABILITY DISTRIBUTION OF ELECTROMAGNETIC WAVE IN VDT ENVIRONMENT BASED ON FUZZY MEASUREMENT DATA UNDER EXISTENCE OF BACKGROUND NOISE

2009 ◽  
Vol 18 ◽  
pp. 365-380
Author(s):  
Hisako Orimoto ◽  
Akira Ikuta
Keyword(s):  
Electromagnetic Wave ◽  
Probability Distribution ◽  
Background Noise ◽  
Measurement Data

scholarly journals Application of a New Combination Algorithm in ELF-EM Processing

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 337
Author(s):  
Fukai Li ◽  
Zhiqiang Yang ◽  
Yehuo Fan ◽  
Yuchun Li ◽  
Guang Li
Keyword(s):  
Electromagnetic Wave ◽  
Measurement Data ◽  
Low Frequency ◽  
New Combination ◽  
Frequency Noise ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Band Noise ◽  
Measurement While Drilling ◽  
Field Noise

With regards to the electromagnetic measurement while drilling (EM-MWD), the extremely-low frequency electromagnetic wave signal (ELF-EM) below 20 Hz is usually used as the carrier of downhole measurement data due to the transmission characteristics of the electromagnetic wave (EM). However, influenced by the low frequency noise of drilling, the ELF-EM signal will be inevitably interfered by field noise, which ultimately impedes decoding. The Fourier band-pass filter can effectively remove out-of-band noise but is incapable of handling in-band noise. Therefore, based on the traditional method, a hybrid algorithm of adaptive Wiener algorithm and correlation detection (AWCD) is designed, so as to enhance the in-band noise processing capability, and the effectiveness of such algorithm is well verified through coding and decoding simulation as well as experimental data. The proposed algorithm, as indicated by theoretical analysis and test data, can effectively solve actual engineering issues, providing methodological references to engineers and technicians.

A new method for path-loss modeling

2019 ◽  
Vol 11 (08) ◽  
pp. 739-746 ◽  
Author(s):  
Qiang Li ◽  
Hongxin Zhang ◽  
Yang Lu ◽  
Tianyi Zheng ◽  
Yinghua Lv
Keyword(s):  
Electromagnetic Wave ◽  
Field Intensity ◽  
Indoor Environment ◽  
Measurement Data ◽  
Path Loss ◽  
Maximum Error ◽  
Measured Data ◽  
Modeling Process ◽  
Multipath Environment ◽  
Path Loss Modeling

AbstractIn this paper, a new path-loss model for electromagnetic wave in an indoor multipath environment is proposed based on matching coefficient, polarization matching factor, and normalized field intensity direction function. This model is called the Friis-extension (Friis-EXT) model, because it operates as the Friis model under certain conditions. In addition, in the modeling process of the path-loss in an indoor environment, the reflective surfaces in the environment and form of the antenna are considered. Afterwards, the path-loss data in an indoor corridor environment are measured, and the maximum error between the theoretical value and the measured data is <7.5 dB. Finally, the Friis-EXT model is compared with some other traditional models, and the results show that the Friis-EXT model is the best one that matches the measurement data.

scholarly journals Quantum circuit cutting with maximum-likelihood tomography

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Michael A. Perlin ◽  
Zain H. Saleem ◽  
Martin Suchara ◽  
James C. Osborn
Keyword(s):  
Maximum Likelihood ◽  
Probability Distribution ◽  
Numerical Experiments ◽  
Measurement Data ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Quantum Devices ◽  
Standard Tool ◽  
Classical Computing

AbstractWe introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit’s fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.

Stochastic Event Detection in Needle-Tissue Interaction

2015 ◽  
Author(s):  
Inki Kim ◽  
Adam Gordon ◽  
Scarlett R. Miller
Keyword(s):  
Probability Distribution ◽  
Event Detection ◽  
Dynamic Models ◽  
Measurement Data ◽  
Gaussian Mixture ◽  
Needle Insertion ◽  
Detection Methods ◽  
Force Model ◽  
Tissue Interactions ◽  
Modes Of Interaction

Over the last decade, many dynamic models that express needle-force relationships under tissues of varying mechanical properties have been developed. While great progress has been made in the development of these high-fidelity models, they are only valid within certain boundary conditions limiting their match with reality. This gap in realism is aggravated by variability in human tissues, needles, and the modes of interaction with the tissue. In an effort to develop more realistic models, the current paper was developed to create and test an event (i.e. changes of variability) detection method based on the probability distribution of residues — difference between force models and measurements. To obtain force measurements, we repeated robotic-driven needle insertion into a simulated mannequin. Needle types and tissue thickness were varied in the measurements in order to add realistic variability. To obtain the force model, the measurement data was used as an input to a Grey-Box model. From the measurements and models, we estimated the probability distribution of residues. For validation, a Gaussian-Mixture Model (GMM) was used to confirm the stochastic model successfully distinguishes the residual distributions under different variability. We found that by examining the residual distributions it is possible to detect unexpected variability in needle-tissue interactions. The findings from this paper have implications for developing real-time event detection methods and simulating patient-variability in haptic applications.

Microdensitometer—computer correlation analysis of ultrastructural periodicity

1978 ◽  
Vol 36 (2) ◽  
pp. 32-33
Author(s):  
D.R. Ensor ◽  
C.G. Jensen ◽  
J.A. Fillery ◽  
R.J.K. Baker
Keyword(s):  
Correlation Analysis ◽  
Background Noise ◽  
Computer Control ◽  
Optical Diffraction ◽  
Screw Thread ◽  
Straight Line ◽  
Computer Storage ◽  
Correlation Process ◽  
Electron Microscope Image ◽  
Fixed Beam

Because periodicity is a major indicator of structural organisation numerous methods have been devised to demonstrate periodicity masked by background “noise” in the electron microscope image (e.g. photographic image reinforcement, Markham et al, 1964; optical diffraction techniques, Horne, 1977; McIntosh,1974). Computer correlation analysis of a densitometer tracing provides another means of minimising "noise". The correlation process uncovers periodic information by cancelling random elements. The technique is easily executed, the results are readily interpreted and the computer removes tedium, lends accuracy and assists in impartiality.A scanning densitometer was adapted to allow computer control of the scan and to give direct computer storage of the data. A photographic transparency of the image to be scanned is mounted on a stage coupled directly to an accurate screw thread driven by a stepping motor. The stage is moved so that the fixed beam of the densitometer (which is directed normal to the transparency) traces a straight line along the structure of interest in the image.

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