mean square


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mean square

[¦mēn ′skwer]
(statistics)
The arithmetic mean of the squares of the differences of a set of values from some given value.
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double dagger]) Ratio of mean square components expressing the relative importance of ([GCA.
Keywords: Least Mean Square (LMS), Variants of LMS, Mean Square Error (MSE), Adaptive Filter, Structure Identification
The description of Root Mean Square Error (RMSE) isrecommended quantification method for the prediction of filters [5].
Bias and Mean square error of ratio type variance estimator was (Eq.
Ventricular late potentials were detected through analysis of filtered QRS complex which characteristically included duration of the filtered QRS complex (fQRS) >114 ms, low amplitude signals (LAS) under 40 uv in the terminal QRS complex >38 ms and root mean square (RMS) voltage in the terminal 40 ms 114 ms in 20 out of total 27 patients in which signal averaged ECG was found positive for detection of ventricular late potentials (p-value 114 ms in higher number of patients with left ventricular hypertrophy in which signal averaged ECG was found positive as compared to those without it(p-value = 0.
The root mean square error (RMSE) and the signal error ratio (SER) are, respectively, defined by
25 pico seconds (ps) root mean square (rms) and integrated electrically erasable programmable read-only memory (EEPROM) for self-configuration at start-up.
The predictive power of the procedures was also evaluated by residual analysis (DRAPER & SMITH, 1966; MONTGOMERY, 2005; MITCHELL & SHEEHY, 1997) and through decomposition of mean square deviation prediction, as suggested by KOBAYASHI & SALAM (2000) as follows:
2]), which is considered universal measure of one random variable dependence on set of others, and the mean square error of approximation that characterizes the approximation of model to statistics in the uniform metric and shows proximity of predicted and experimental data.
9 Mean forecast error Mean absolute error Mean squared error Root mean square forecast error Score (Percentage of times Forecast 1 performs better) Diebold Mariano statistic Forecast 1 against forecast 2 relative to first outturn Year (a) Naive First NIESR forecast outturn forecast year ahead 1990 4.
Greater SCA mean square revealed that time to 50% flowering was controlled non-additively.
There are many adaptive algorithms that could be used in echo cancellation for adaptive filtering including wiener filter, steepest descent method, least mean square, normalized least mean square and recursive least squares [7] and [8], However, a generic block diagram of any adaptive filtering is given as figure 3.