Sentence examples for pattern and p from inspiring English sources

R^{2} = { 1} - ;left( {frac{{mathop sum nolimits_{j} left( {tj - oj} right)^{2} }}{{mathop sum nolimits_{j} left( {oj} right)^{2} }}} right) (4) MAPE = frac{1}{text{P}} mathop sum limits_{text{j}} left( {left| {left. {frac{oj - tj}{oj}} right|} right. *100} right), (5 where tj is the target value of jth pattern, oj is the output value of jth pattern, and p is the number of patterns.

A match of s i and s j can occur in various ways, each of which can be described as the tuple (y, p ), where y = y1,…, y b − d describe the blocks in the pattern and p is the offset with which the pattern matches s j.

In this patient, out of 33 analysed PV automaticity beats with an LA PV coupling interval ranging from 56 to 1088 ms, 15 beats did capture the LA with the shortest coupling interval being 320 ms. Capture of the LA by PV beats was characterized by a consistent change in CS activation pattern and P-wave.

where P X X ) is the probability density of the input spike patterns and P w ( Y | X ) = ∏ ν = 1 N P w ⋅, ν ( Y ν | X ).

where t p denotes the time duration assigned to a pattern p, and P is the set containing all patterns.

Similarly, the scores assigned by the two pathologists were highly correlated for the two staining patterns, with a correlation coefficient (r) of 0.92 (P < 0.001) for the diffuse cytoplasmic pattern and 0.95 (P < 0.001) for the number of positive SLS.

Figure 3 (upper panel) shows the XRD patterns of the pristine DMHCS (pattern a) and Pd nanoparticle-decorated DMHCS (patterns: b Pd-I1, c Pd-R1, d Pd-I2, e Pd-R2).

Significant changes were seen in group 2 after four hours concerning the amplitude for the 1°18' and 17.7' pattern (p = 0.028 and 0.08) and the peak time of the 35.4' pattern (p = 0.038).

Sensors featuring these p-stop patterns and the p-spray blocking method were tested in a 120 GeV/c hadron beam at the SPS at CERN, γ-irradiated to 100 kGy at SCK-CEN (Mol, Belgium), and immediately afterwards tested again at CERN in the same setup as before.

n{ p } is the number of cases with the pth pattern and ∑ n{ p } = N.

It follows that is the J{ p } × 1 vector of ML estimates corresponding to the p th pattern and is the corresponding J{ p } × J{ p } covariance matrix with a correction for degrees of freedom.