Characterization of antennas for mobile and wireless terminals by using reverberation chambers: improved accuracy by platform stirring

2002 ◽  
Author(s):  
K. Rosengren ◽  
P.-S. Kildal ◽  
C. Carlsson ◽  
J. Carlsson
Keyword(s):  
Reverberation Chambers ◽  
Improved Accuracy

Characterization of antennas for mobile and wireless terminals in reverberation chambers: Improved accuracy by platform stirring

2001 ◽  
Vol 30 (6) ◽  
pp. 391-397 ◽  
Author(s):  
Kent Rosengren ◽  
Per-Simon Kildal ◽  
Charlie Carlsson ◽  
Jan Carlsson
Keyword(s):  
Reverberation Chambers ◽  
Improved Accuracy

scholarly journals Change point detection with multiple alternatives reveals parallel evaluation of the same stream of evidence along distinct timescales

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexa Booras ◽  
Tanner Stevenson ◽  
Connor N. McCormack ◽  
Marie E. Rhoads ◽  
Timothy D. Hanks
Keyword(s):  
Change Point ◽  
Neural Mechanism ◽  
Detection Task ◽  
Change Point Detection ◽  
Model Free ◽  
Evidence Evaluation ◽  
Parallel Evaluation ◽  
Point Detection ◽  
Improved Accuracy

AbstractIn order to behave appropriately in a rapidly changing world, individuals must be able to detect when changes occur in that environment. However, at any given moment, there are a multitude of potential changes of behavioral significance that could occur. Here we investigate how knowledge about the space of possible changes affects human change point detection. We used a stochastic auditory change point detection task that allowed model-free and model-based characterization of the decision process people employ. We found that subjects can simultaneously apply distinct timescales of evidence evaluation to the same stream of evidence when there are multiple types of changes possible. Informative cues that specified the nature of the change led to improved accuracy for change point detection through mechanisms involving both the timescales of evidence evaluation and adjustments of decision bounds. These results establish three important capacities of information processing for decision making that any proposed neural mechanism of evidence evaluation must be able to support: the ability to simultaneously employ multiple timescales of evidence evaluation, the ability to rapidly adjust those timescales, and the ability to modify the amount of information required to make a decision in the context of flexible timescales.

scholarly journals Change point detection with multiple alternatives reveals parallel evaluation of the same stream of evidence along distinct timescales

2020 ◽  
Author(s):  
Alexa Booras ◽  
Tanner Stevenson ◽  
Connor N. McCormack ◽  
Marie E. Rhoads ◽  
Timothy D. Hanks
Keyword(s):  
Change Point ◽  
Neural Mechanism ◽  
Detection Task ◽  
Change Point Detection ◽  
Model Free ◽  
Evidence Evaluation ◽  
Parallel Evaluation ◽  
Point Detection ◽  
Improved Accuracy

AbstractIn order to behave appropriately in a rapidly changing world, individuals must be able to detect when changes occur in that environment. However, at any given moment, there are a multitude of potential changes of behavioral significance that could occur. Here we investigate how knowledge about the space of possible changes affects human change point detection. We used a stochastic auditory change point detection task that allowed model-free and model-based characterization of the decision process people employ. We found that subjects can simultaneously apply distinct timescales of evidence evaluation to the same stream of evidence when there are multiple types of changes possible. Informative cues that specified the nature of the change led to improved accuracy for change point detection through mechanisms involving both the timescales of evidence evaluation and adjustments of decision bounds. These results establish three important capacities of information processing for decision making that any proposed neural mechanism of evidence evaluation must be able to support: the ability to simultaneously employ multiple timescales of evidence evaluation, the ability to rapidly adjust those timescales, and the ability to modify the amount of information required to make a decision in the context of flexible timescales.

PRESTACK SEISMIC INVERSION WITH STRUCTURAL CONSTRAINTS

2021 ◽  
pp. 1-41
Author(s):  
Dong Li ◽  
Suping Peng ◽  
rui Zhang ◽  
Yinling Guo ◽  
Yongxu Lu ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Structural Constraints ◽  
Local Smoothing ◽  
Data Noise ◽  
Improved Accuracy ◽  
Prestack Seismic Inversion ◽  
Influence Of Noise

Pre-stack seismic inversion usually suffers from the lower signal-to-noise ratio, which could result in unstable inversion results. The conventional multi-trace lateral constrained inversion blurs the steeply dipping layers, whereas the simple structural constrained inversion is affected by noise. To solve this issue, an inversion method with multiple constraints is proposed, which include 1) A local smoothing operator is used to suppress the inversion anomalies caused by data noise, 2) a difference operator is used to protect the stratum boundary, 3) a structural dipping constraint is used to enhance the characterization of the possible dipping stratum. The multi-constraint inversion method suppresses the inversion anomalies caused by data noise without blurring the stratum boundary. The effects of different constraints in the inversion process and the influence of noise on the inversion results are analyzed. In multi-constraint inversion, the regularization coefficient of each constraint operator is dynamically changed, thereby controlling the significance of each regularization term in the inversion. The proposed algorithm is tested on synthetic and field data, which demonstrates its effectiveness and improved accuracy on the inversion results.

Characterization Improvement Through Signal Processing: Application to Radiography Inspection — 3D Reconstruction

2005 ◽  
Author(s):  
Laurence Chatellier ◽  
Valery E. Just ◽  
Louis Fournier ◽  
Bruno Charbonnier ◽  
Lionel Robillard
Keyword(s):  
Signal Processing ◽  
3D Reconstruction ◽  
Incidence Angle ◽  
Vertical Direction ◽  
Regulatory Requirements ◽  
Reconstruction Process ◽  
Processing Application ◽  
Improved Accuracy ◽  
Service Inspection

During in-service inspections, experts are faced with the delicate task of establishing a complete diagnosis of defects from radiographs. Should a defect be detected, one must be able to demonstrate that the component still meets regulatory requirements. Thus, it is essential to be able to characterize precisely the defect, especially when the demonstration relies on mechanical calculus. However the characterization of the defect by only g or X-ray is sometimes very difficult, and the justification process can thus be jeopardized. In such cases, signal processing can be very helpful for the interpretation of the data and for the characterization (positioning and sizing) of the defect. This paper presents a 3-D reconstruction processing in hard conditions representatives of pipe inspections: the incidence angle is very reduced and thus the radiographs contain very little information along the vertical direction. The reconstruction process relies on the estimation of the attenuation. It is called inversion because it restores the attenuation from both data and prior information. The method has been tested on radiographs of a block with real defects and the performances were evaluated from a mock-up with several electro-drilled cylindrical defects. Even in the case of limited incidence, the method provides very useful 3D results. Moreover this process can be applied whatever the nature of the source. When a larger source is used in order to inspect thick components, signal processing allows to reduce the inevitable blur which leads to improved accuracy. In conclusion, signal processing and especially 3D reconstruction in the case of radiography can turn out to be a key step fur in-service inspection of major NPP components.

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