Mean-Square Error Analysis of a Non-Uniform Subband Adaptive Filtering Structure with Critical Sampling

2007 ◽  
Author(s):  
Mariane R. Petraglia ◽  
Paulo B. Batalheiro
Keyword(s):  
Error Analysis ◽  
Mean Square Error ◽  
Adaptive Filtering ◽  
Mean Square

Time-Domain Filtering of Two-Dimensional Fluorescence Data

1986 ◽  
Vol 40 (4) ◽  
pp. 542-548 ◽  
Author(s):  
Maria Vicsek ◽  
Sharon L. Neal ◽  
Isiah M. Warner
Keyword(s):  
Error Analysis ◽  
Mean Square Error ◽  
Time Domain ◽  
Moving Average ◽  
Mean Square ◽  
Two Dimensional ◽  
Spline Method ◽  
Dimensional Version ◽  
The Difference ◽  
Polynomial Smoothing

Four time-domain filtering methods are applied to simulated and experimental two-dimensional fluorescence data in order to evaluate their performance. The methods that were evaluated are (1) moving average, (2) Savitsky-Golay polynomial smoothing, (3) Chebyshev filtering, and (4) bicubic spline filtering. The methods are compared with the use of mean square error analysis and the difference in the amplitudes of the filtered noisy and ideal data. The two-dimensional version of the Savitzky-Golay filtering and the spline method produced the best overall results.

Recursive inverse algorithm: Mean-square-error analysis

2017 ◽  
Vol 66 ◽  
pp. 10-17 ◽  
Author(s):  
Mohammad Shukri Salman ◽  
Osman Kukrer ◽  
Aykut Hocanin
Keyword(s):  
Error Analysis ◽  
Mean Square Error ◽  
Mean Square ◽  
Inverse Algorithm
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