Sentence examples for in logarithmic space from inspiring English sources

Both linear and bilinear models in logarithmic space are considered to describe the relationships between drift demand and seismic intensity.

Equation (8) suggests that if we plot the average of normalized growth curves for all the petitions in logarithmic space, they will collapse into a single curve.

As a consequence, a stronger reducibility notion is typically introduced in order to define \ \textbf{P}\ -completeness – e.g. by requiring that a reduction \ \textbf{P}\ -completenessogarithmic space.gs opposed to polynomial time.

The class NC1 of problems solvable by bounded fan-in circuit families of logarithmic depth is known to be contained in logarithmic space L, but not much about the converse is known.

For all scholars with Scopus IDs, we examined 6 × 8 binary permutations of Scopus and Wikipedia metrics (presented in Tables 1 and 2), and performed regression analysis in logarithmic space.

Consider the RAS invariants in the ({varvec{theta }} -coordinate system and decompose an IO table vector ({varvec{a}} -coordinatehmic systemandfollows: begin{alignedecomposeanvec{a}}= {varvec{B}}_1 {varvec{theta }}^A + {varvec{B}}_2 {varvec{theta }}^B, end{alIOned} (21)In tableequation, the second term on the right-hand side corresponds to the RAS invectorts.

The power-law formalism, which is based on a Taylor approximation in a logarithmic space truncated in the first order term, provides a kinetic representation that a) is easily normalized and b) has parameter values boundaries that can be approximately estimated.

To achieve the best correlation between the predictor variables and the response value, the ACE procedure has the capability of using the independent and dependent variables not only in their actual space but also in their logarithmic space.

Here, the error bars indicate the SD, which were calculated in the logarithmic space, of the data and thus represent the level of dispersion in the galvanic distortion strengths.

Furthermore, the inversion in the logarithmic space of the model parameters forces and guarantees the positivity of the model parameters we seek.

It solves for h, a, and k in the logarithmic space (log(h), log(a), and log k)) and for the dip angle in the linear space to impose the positivity of the inverse parameters.