Positioning of Mobile Terminals based on Feature Extraction from Channel Impulse Responses

2006 ◽  
Author(s):  
M. Layh ◽  
U. Reiser ◽  
D. Zimmermann ◽  
F. Landstorfer
Keyword(s):  
Feature Extraction ◽  
Impulse Responses ◽  
Mobile Terminals

scholarly journals Research on the Sparse Representation for Gearbox Compound Fault Features Using Wavelet Bases

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Chunyan Luo ◽  
Changqing Shen ◽  
Wei Fan ◽  
Gaigai Cai ◽  
Weiguo Huang ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Fault Diagnosis ◽  
Sparse Representation ◽  
Background Noise ◽  
Practical Application ◽  
Impulse Responses ◽  
Wavelet Bases ◽  
Potential Approach ◽  
Fault Features ◽  
Engineering Practices

The research on gearbox fault diagnosis has been gaining increasing attention in recent years, especially on single fault diagnosis. In engineering practices, there is always more than one fault in the gearbox, which is demonstrated as compound fault. Hence, it is equally important for gearbox compound fault diagnosis. Both bearing and gear faults in the gearbox tend to result in different kinds of transient impulse responses in the captured signal and thus it is necessary to propose a potential approach for compound fault diagnosis. Sparse representation is one of the effective methods for feature extraction from strong background noise. Therefore, sparse representation under wavelet bases for compound fault features extraction is developed in this paper. With the proposed method, the different transient features of both bearing and gear can be separated and extracted. Both the simulated study and the practical application in the gearbox with compound fault verify the effectiveness of the proposed method.

An Improved Quantitative Image Analyser

1977 ◽  
Vol 35 ◽  
pp. 226-227
Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Frequency Content ◽  
General Sense ◽  
Physical Measurements ◽  
Quantitative Image ◽  
Image Analyser ◽  
Automatic Methods ◽  
Quantitative Results

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.

Following the time course of feature extraction with event-related brain potentials

1996 ◽  
Author(s):  
Lourdes Anllo-Vento ◽  
Steven A. Hillyard
Keyword(s):  
Feature Extraction ◽  
Time Course ◽  
Brain Potentials
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