A fast search for the maximum element of the fourier spectrum

2005 ◽  
pp. 134-141
Author(s):  
Alexey E. Ashikhmin ◽  
Simon N. Litsyn
Keyword(s):  
Fourier Spectrum ◽  
Maximum Element ◽  
Fast Search

Electron holography in materials science

1991 ◽  
Vol 49 ◽  
pp. 670-671
Author(s):  
Hannes Lichte ◽  
Edgar Voelkl
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Materials Science ◽  
Fourier Spectrum ◽  
Object Wave ◽  
Electron Holography ◽  
Reconstruction Procedure ◽  
Numerical Reconstruction ◽  
Transmission Electron ◽  
Unique Interpretation

The object wave o(x,y) = a(x,y)exp(iφ(x,y)) at the exit face of the specimen is described by two real functions, i.e. amplitude a(x,y) and phase φ(x,y). In stead of o(x,y), however, in conventional transmission electron microscopy one records only the real intensity I(x,y) of the image wave b(x,y) loosing the image phase. In addition, referred to the object wave, b(x,y) is heavily distorted by the aberrations of the microscope giving rise to loss of resolution. Dealing with strong objects, a unique interpretation of the micrograph in terms of amplitude and phase of the object is not possible. According to Gabor, holography helps in that it records the image wave completely by both amplitude and phase. Subsequently, by means of a numerical reconstruction procedure, b(x,y) is deconvoluted from aberrations to retrieve o(x,y). Likewise, the Fourier spectrum of the object wave is at hand. Without the restrictions sketched above, the investigation of the object can be performed by different reconstruction procedures on one hologram. The holograms were taken by means of a Philips EM420-FEG with an electron biprism at 100 kV.

Image thresholding method based on Fourier spectrum and moment-preserving principle

2010 ◽  
Vol 30 (8) ◽  
pp. 2094-2097 ◽  
Author(s):  
Xin-ming ZHANG ◽  
Shuang LI ◽  
Yan-bin ZHENG ◽  
Hui-yun ZHANG
Keyword(s):  
Fourier Spectrum ◽  
Image Thresholding ◽  
Thresholding Method

scholarly journals Fast Search Method Based on Vector Quantization for Raman Spectroscopy Identification

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1970
Author(s):  
Jun-Kyu Park ◽  
Suwoong Lee ◽  
Aaron Park ◽  
Sung-June Baek
Keyword(s):  
Search Algorithm ◽  
Principal Component ◽  
Search Method ◽  
Reference Spectrum ◽  
Search Range ◽  
Fast Search ◽  
Input Spectrum ◽  
Computationally Intensive ◽  
Multiple Clusters ◽  
Full Search

In spectroscopy, matching a measured spectrum to a reference spectrum in a large database is often computationally intensive. To solve this problem, we propose a novel fast search algorithm that finds the most similar spectrum in the database. The proposed method is based on principal component transformation and provides results equivalent to the traditional full search method. To reduce the search range, hierarchical clustering is employed, which divides the spectral data into multiple clusters according to the similarity of the spectrum, allowing the search to start at the cluster closest to the input spectrum. Furthermore, a pilot search was applied in advance to further accelerate the search. Experimental results show that the proposed method requires only a small fraction of the computational complexity required by the full search, and it outperforms the previous methods.

Optimization of the Robots Fourier Spectrum by Using the Assisted Research, Neural Network, Smart Damper and LabVIEW Instrumentation

2012 ◽  
Vol 245 ◽  
pp. 24-32 ◽  
Author(s):  
Adrian Olaru ◽  
Serban Olaru ◽  
Aurel Oprean
Keyword(s):  
Neural Network ◽  
Transfer Function ◽  
Spectral Density ◽  
Vibration Analysis ◽  
Manufacturing Systems ◽  
Fourier Spectrum ◽  
Industrial Robots ◽  
Vibration Behavior ◽  
Power Spectral ◽  
The World

The most important things in the dynamic research of industrial robots are the vibration behavior, the transfer function and the vibration power spectral density between some of the robot joints and components. In the world this research is made without the assisted research. In each of the study cases in this paper was used the proper virtual Fourier analyzer and was presented one new method of the assisted vibration analysis. With this research it is possible the optimal choosing the base modulus type to avoid the frequencies from the robot spectrum. In the manufacturing systems, the most important facts are the vibration behavior of the robot, the compatibility with some other components of the system. All the VI where achieved in the LabVIEW soft 8.2 version, from National Instruments, USA. This method and the created virtual LabVIEW instrumentation are generally and they are possible to apply in many other dynamic behavior research.

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