scholarly journals Wavelet Multiresolution Analysis of the Liquidity Effect and Monetary Neutrality

2017 ◽  
Vol 53 (1) ◽  
pp. 85-110 ◽  
Author(s):  
Olivier Habimana
Keyword(s):  
Multiresolution Analysis ◽  
Liquidity Effect ◽  
Wavelet Multiresolution Analysis ◽  
Monetary Neutrality

Driver's Mental Stress Visualization by Discrete Wavelet Multiresolution Analysis.

2000 ◽  
Vol 20 (79) ◽  
pp. 356-364
Author(s):  
Taro SEKINE ◽  
Masahiro TAKEI ◽  
Michiharu OKANO ◽  
Hiroyasu NAGAE ◽  
Yoshifuru SAITO ◽  
...  
Keyword(s):  
Multiresolution Analysis ◽  
Mental Stress ◽  
Discrete Wavelet ◽  
Wavelet Multiresolution Analysis

Monitoring HVDC Systems Using Wavelet Multiresolution Analysis

2001 ◽  
Vol 21 (11) ◽  
pp. 54-55 ◽  
Author(s):  
A. M. Gouda ◽  
E. F. El-Saadany ◽  
M. M. A. Salama ◽  
V. K. Sood ◽  
A. Y. Chikhani
Keyword(s):  
Multiresolution Analysis ◽  
Wavelet Multiresolution Analysis

Nonlinear Aerodynamics Reduced-Order Model Based on Multi-Input Volterra Series

2013 ◽  
Vol 748 ◽  
pp. 421-426 ◽  
Author(s):  
Yi Bin Dou ◽  
Min Xu
Keyword(s):  
Multiresolution Analysis ◽  
Volterra Series ◽  
Coupling Effect ◽  
Harmonic Oscillation ◽  
Reduced Order Model ◽  
Least Square ◽  
Recursive Least Square ◽  
Order Model ◽  
Reduced Order ◽  
Wavelet Multiresolution Analysis

This paper gives a low-order approximations of multi-input Volterra series as a nonlinear reduced-order model (ROM) based on wavelet multiresolution analysis. The band-limited pseudorandom multilevel sequence (PRMS) is used as the identification signal and the QR decomposition recursive least square (QRD-RLS) method is utilized as identification method. At last, the ROM is applied to model the nonlinear aerodynamic moment of an airfoil undergoing simultaneous forced pitch and plunge harmonic oscillation. The results show that including the second-order Volterra cross kernels in ROM can capture the coupling effect which significantly improves accuracy in predicting nonlinear aerodynamics under simultaneous motion. And the wavelet multiresolution analysis efficiently reduces the number of identification coefficients for Volterra kernels.

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