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The EMG signals were smoothed with a root mean square function with a 50 msec sliding window and the area under the processed signals was integrated within five seconds, during which the pre-manipulative stretch was maintained in order to provide quantitative measures of the amount of muscular activation.
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By substituting ( t_{1} = t_{2} = t ) into (108) and (109), it is straightforward to find second moment functions, i.e., the mean square functions of the random response.
Let (g:Ilongrightarrow L_{2}) be a mean square bounded function and let (h>0), then the mean square modulus of continuity of g is the function omega g,h)= sup_{|t-t^|leq h}{bigl| g(t -gbigl(t -gbiglbigr| },quad t^bigr I.
Here, we also find its gain and estimate the initial mean square state function.
The OFIR filter self-determines the initial mean square state function by solving the discrete algebraic Riccati equation.
If a sufficient number of valid correspondences are available, then the geometric transformation can be estimated by minimizing the mean square difference function.
A root mean square (RMS) function was used to analyze the jerk variation.
The network training is based on the weighted mean square error cost function, allowing us to use the marginal probability of each pattern viewed by a given window.
These points are compared resulting in the mean square error cost function (MMSE) (3) The most likely location is determined by minimizing this cost function [57, 58]: (3).
A maximum likelihood algorithm with a mean square error cost function has a position error median of 6.66 m.
A maximum likelihood algorithm with a mean square error cost function has a higher position error median than our algorithm.
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