Synonyms for unnormalized or Related words with unnormalized
Examples of "unnormalized"
form over normalized forms are -
modified KdV equation is a nonlinear partial differential equation：
KdV equation is a Nonlinear partial differential equation
where the (
) sinc function is defined by formula_57.
lexicographic ordering would order these sequences thus: #3, #5, #4, #1, #2.
In mathematics, the historical
sinc function is defined for by
This value is the forward
probability vector. The i'th entry of this vector provides:
All sums in this section refer to the
"P" represents the set of
probability distributions over player 1’s
where formula_74 is the sum of the
weights. In this case formula_74 is simply
using angular frequency ω, where formula_6 is the
form of the sinc function.
In all cases, the ranking given by the geometric mean stays the same as the one obtained with
Equivalently, the Jeffreys prior for formula_32 is the
uniform distribution on the non-negative real line.
In addition to the above "
" architecture, RBF networks can be "normalized". In this case the mapping is
sinc "α" is the
cardinal sine function (with the discontinuity removed). In his proposal, Winkel set :
The above dispersive Gaussian wave packet,
and just centered at the origin, instead, at =0, can now be written in 3D:
Its most novel feature was
significance arithmetic floating point. This allowed users to determine the change in precision of results due to the nature of the computation.
where sinc is the
sinc function and formula_12 is one of the imaginary, zero or real square roots of "k". These definitions are valid for all "k".
where formula_3 are independent Wiener processes. Then the
conditional probability density formula_4 of the state at time t is given by the Zakai equation:
where the learning rate formula_79 is again taken to be 0.3. The training is performed with one pass through the 100 training points. The rms error on a test set of 100 exemplars is 0.084, smaller than the
error. Normalization yields accuracy improvement. Typically accuracy with normalized basis functions increases even more over
functions as input dimensionality increases.
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