scholarly journals Creation and annihilation of point-potentials using Moutard-type transform in spectral variable

2020 ◽  
Vol 61 (9) ◽  
pp. 093501
Author(s):  
P. G. Grinevich ◽  
R. G. Novikov
Keyword(s):  
Spectral Variable

Detection of chlorophyll content in growth potato based on spectral variable analysis

2020 ◽  
Vol 53 (6) ◽  
pp. 476-488 ◽  
Author(s):  
Ning Liu ◽  
Lang Qiao ◽  
Zizheng Xing ◽  
Minzan Li ◽  
Hong Sun ◽  
...  
Keyword(s):  
Chlorophyll Content ◽  
Spectral Variable ◽  
Variable Analysis

FATIGUE CONTRACTION ANALYSIS USING EMPIRICAL MODE DECOMPOSITION AND WAVELET TRANSFORM

2015 ◽  
Vol 77 (6) ◽  
Author(s):  
Rubana Haque Chowdhury ◽  
Mamun Bin Ibne Reaz
Keyword(s):  
Wavelet Transform ◽  
Muscle Fatigue ◽  
Empirical Mode Decomposition ◽  
Surface Emg ◽  
Semg Signal ◽  
Emg Signal ◽  
Mode Decomposition ◽  
Spectral Variable ◽  
Walking Exercise ◽  
The Difference

Muscle fatigue is a long lasting reduction of the ability to contract and it is the condition when produced force is reduced. Walking fast can cause muscle fatigue, which is unhealthy and it is incurable when the level of fatigue is high. Muscle fatigue during walk can be determined using several spectral variables. The amplitude and frequency of the surface EMG signal provide a more accurate reflection of motor unit pattern among these spectral variables. This research reports on the effectiveness of Empirical mode decomposition (EMD) and wavelet transform based filtering method applied to the surface EMG (sEMG) signal as a means of achieving reliable discrimination of the muscle fatigue during human walking exercise. In this research, IAV, RMS and AIF values were used as spectral variable. These spectral variables extensively identifies the difference between fatigue and normal muscle when using EMD method compared with other different wavelet functions (WFs). The result shows that the sEMG amplitude and frequency momentously changes from rest position to maximum contraction position.

A modification of the successive projections algorithm for spectral variable selection in the presence of unknown interferents

2011 ◽  
Vol 689 (1) ◽  
pp. 22-28 ◽  
Author(s):  
Sófacles Figueredo Carreiro Soares ◽  
Roberto Kawakami Harrop Galvão ◽  
Mário César Ugulino Araújo ◽  
Edvan Cirino da Silva ◽  
Claudete Fernandes Pereira ◽  
...  
Keyword(s):  
Variable Selection ◽  
Successive Projections Algorithm ◽  
Spectral Variable ◽  
Successive Projections

Generalized Two-Dimensional Correlation Method Applicable to Infrared, Raman, and other Types of Spectroscopy

1993 ◽  
Vol 47 (9) ◽  
pp. 1329-1336 ◽  
Author(s):  
I. Noda
Keyword(s):  
Correlation Method ◽  
External Perturbation ◽  
Data Sets ◽  
Two Dimensional ◽  
Electromagnetic Probe ◽  
Wide Range ◽  
Potential Applications ◽  
Spectral Variable ◽  
Spectroscopic Tool ◽  
Ir And Raman

A two-dimensional (2D) correlation method generally applicable to various types of spectroscopy, including IR and Raman spectroscopy, is introduced. In the proposed 2D correlation scheme, an external perturbation is applied to a system while being monitored by an electromagnetic probe. With the application of a correlation analysis to spectral intensity fluctuations induced by the perturbation, new types of spectra defined by two independent spectral variable axes are obtained. Such two-dimensional correlation spectra emphasize spectral features not readily observable in conventional one-dimensional spectra. While a similar 2D correlation formalism has already been developed in the past for analysis of simple sinusoidally varying IR signals, the newly proposed formalism is designed to handle signals fluctuating as an arbitrary function of time, or any other physical variable. This development makes the 2D correlation approach a universal spectroscopic tool, generally applicable to a very wide range of applications. The basic property of 2D correlation spectra obtained by the new method is described first, and several spectral data sets are analyzed by the proposed scheme to demonstrate the utility of generalized 2D correlation spectra. Potential applications of this 2D correlation approach are then explored.

scholarly journals Spectral densities of singular values of products of Gaussian and truncated unitary random matrices

2019 ◽  
Vol 09 (04) ◽  
pp. 2050014
Author(s):  
Thorsten Neuschel
Keyword(s):  
Singular Values ◽  
Integral Representations ◽  
Algebraic Equations ◽  
Unitary Matrices ◽  
New Approach ◽  
Special Cases ◽  
Spectral Variable ◽  
Dimensional Growth ◽  
Complex Integral ◽  
Stieltjes Transforms

We study the densities of limiting distributions of squared singular values of high-dimensional matrix products composed of independent complex Gaussian (complex Ginibre) and truncated unitary matrices which are taken from Haar distributed unitary matrices with appropriate dimensional growth. In the general case, we develop a new approach to obtain complex integral representations for densities of measures whose Stieltjes transforms satisfy algebraic equations of a certain type. In the special cases in which at most one factor of the product is a complex Gaussian, we derive elementary expressions for the limiting densities using suitable parameterizations for the spectral variable. Moreover, in all cases we study the behavior of the densities at the boundary of the spectrum.

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