Blind signal detection and parameter estimation for an asynchronous CDMA system with time-varying number of transmission paths

2002 ◽  
Author(s):  
C. Carlemalm ◽  
A. Logothetis
Keyword(s):  
Parameter Estimation ◽  
Signal Detection ◽  
Cdma System ◽  
Time Varying ◽  
Blind Signal ◽  
Asynchronous Cdma

scholarly journals Accurate signal detection for BPSK-OFDM systems in time-varying channels

2017 ◽  
Vol 60 ◽  
pp. 370-379 ◽  
Author(s):  
Min Huang ◽  
Lei Huang ◽  
Weize Sun ◽  
Jihong Zhang ◽  
Hing Cheung So
Keyword(s):  
Signal Detection ◽  
Time Varying ◽  
Ofdm Systems ◽  
Time Varying Channels

scholarly journals Wavelet multi-resolution approximation of time-varying frame structure

2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879559 ◽  
Author(s):  
Min Xiang ◽  
Feng Xiong ◽  
Yuanfeng Shi ◽  
Kaoshan Dai ◽  
Zhibin Ding
Keyword(s):  
Parameter Estimation ◽  
Degrees Of Freedom ◽  
Structural Parameters ◽  
Identification Problem ◽  
Frame Structure ◽  
Structural Parameter ◽  
Time Varying ◽  
Engineering Structures ◽  
Time Frequency ◽  
Non Parametric

Engineering structures usually exhibit time-varying behavior when subjected to strong excitation or due to material deterioration. This behavior is one of the key properties affecting the structural performance. Hence, reasonable description and timely tracking of time-varying characteristics of engineering structures are necessary for their safety assessment and life-cycle management. Due to its powerful ability of approximating functions in the time–frequency domain, wavelet multi-resolution approximation has been widely applied in the field of parameter estimation. Considering that the damage levels of beams and columns are usually different, identification of time-varying structural parameters of frame structure under seismic excitation using wavelet multi-resolution approximation is studied in this article. A time-varying dynamical model including both the translational and rotational degrees of freedom is established so as to estimate the stiffness coefficients of beams and columns separately. By decomposing each time-varying structural parameter using one wavelet multi-resolution approximation, the time-varying parametric identification problem is transformed into a time-invariant non-parametric one. In solving the high number of regressors in the non-parametric regression program, the modified orthogonal forward regression algorithm is proposed for significant term selection and parameter estimation. This work is demonstrated through numerical examples which consider both gradual variation and abrupt changes in the structural parameters.

Sign in / Sign up

Export Citation Format

Share Document