Your English writing platform
Discover LudwigSuggestions(1)
Exact(1)
Let us assume the spectrum to be normalized is defined as a vector 'S' and the normalized spectrum as a vector 'SN' where S = left({s}_1,{s}_2,dots, {s}_Nright).
Similar(59)
The inputs are are normalized and are defined as follows: z_{t - d} = {{left[ {varepsilon_{t - d} - Eleft( varepsilon right)} right]} mathord{left/ {vphantom {{left[ {varepsilon_{t - d} - Eleft( varepsilon right)} right]} {sqrt {Eleft( {varepsilon^{2} } right)} }}} right.
The normalized amplitude is defined as,,, where is the average energy of the signal.
The normalized threshold is defined by (42).
The normalized signal is defined as follows: (9).
The normalized displacement is defined as the distance from the axon center divided by its diameter.
In addition, (R_s) is the normalized coefficient that is defined by begin{aligned} R_s = dfrac{1}{2}mathop {text {argmin}}limits _{c_1,c_2in varvec{C}}(ln (mathrm{len}(c_1,c_2)/2D)).
The convergence state of adaptive filter is evaluated with the normalized misalignment which is defined as 20log_{10}left(frac{Vertmathbf{h}-hat{mathbf{h}}Vert_{2}}{Vertmathbf{h}Vert_{2}}right).
In the plot, the normalized capacity loss is defined to be the distortion ratio of correlated fading channels over i.i.d.i.d
where μ m,i (t − 1) represents the i th model probability of the m th AN at time step t − 1, p ij denotes the transition probability defined in Markov chain, and c ¯ m, j is a normalized variable, which is defined as c ¯ m, j = ∑ i = 1 2 p ij u m, i t − 1. (13).
The normalized duality mapping is defined as (1.1).
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com