IQ mismatch compensation using time domain signal processing: A practical approach

Author(s):  
Bijoy Bhukania ◽  
Sthanunathan Ramakrishnan ◽  
Yogesh Darwhekar
2012 ◽  
Vol 47 (3) ◽  
pp. 127-136
Author(s):  
Waldemar Popiński

Statistical View on Phase and Magnitude Information in Signal ProcessingIn this work the problem of reconstruction of an original complex-valued signalot,t= 0, 1, …,n- 1, from its Discrete Fourier Transform (DFT) spectrum corrupted by random fluctuations of magnitude and/or phase is investigated. It is assumed that the magnitude and/or phase of discrete spectrum values are distorted by realizations of uncorrelated random variables. The obtained results of analysis of signal reconstruction from such distorted DFT spectra concern derivation of the expected values and bounds on variances of the reconstructed signal at the observation moments. It is shown that the considered random distortions in general entail change in magnitude and/or phase of the reconstructed signal expected values, which together with imposed random deviations with finite variances can blur the similarity to the original signal. The effect of analogous random amplitude and/or phase distortions of a complex valued time domain signal on band pass filtration of distorted signal is also investigated.


2013 ◽  
Vol 436 ◽  
pp. 287-294
Author(s):  
Bogdan Betea ◽  
Liviu Tomesc

On this paper a bearing defects diagnosis method is introduced. This diagnosis method is based on time domain signal processing first step being the kurtosis based filtering. This filtering is based on the detection of the shock pulses generated by bearing defects. The diagnosis is done using the detected defects periods which are the inputs for a fuzzy classifier that provide defect alerts for each kind of bearing localize defect


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