The phrase "approximation input" is correct and usable in written English.
It can be used in contexts related to data processing, algorithms, or mathematical modeling where an input value is not exact but rather an estimate.
Example: "The algorithm requires an approximation input to generate a preliminary result before refining it with more accurate data."
Alternatives: "estimated input" or "approximate value".
To conclude, the main stages of converting a sequence of source vectors are summarized in Table 2. Table 2 Voice conversion using GB approximation Input: a sequence of feature vectors related to the source speaker x 1 T Initialization: set the initial weights, (left {w_{0|0}^{k}right }_{k=1}^{N_{y}}).
Table 1 Bayesian estimation using grid-based approximation Input: a sequence of states sampled from the observed process x 1 T Initialization: set the initial weights, (left {w_{0|0}^{k}right }_{k=1}^{N_{y}}), using Eq. (13) Main iteration: for t=1,…T, perform the following steps: 1. Evaluate the prior weights, (left {w_{t|t-1}^{k}right }_{k=1}^{N_{y}}), using Eq. (10).
It is also required to find a suitable approximation between input variables and responses.
The activation of output layer is given as below: begin{aligned} hat{x}_{l}=f(W_2 a_h+B_2), end{aligned} (3)where the (hat{x}_{l}^{(i }in {R^m}) is output vector, a nonlinear approximation of input vector (x_{l}^{(i)}).
It means that the results of the MC-Net algorithm give better approximation for input distance vector.
The multi-layered network generally uses for accomplishing the global approximation of input-output mapping but sometimes getting stuck into local minima, while the nonlinear radial basis function (RBF) network is based on exponentially decaying that uses for local approximation to input-output mapping.
The simulated network is a simple approximation of inputs and recurrent connections to a patch of cortex.
Using any of these bases to approximate the input signal generates approximation error.
Weyl defined real functions as mappings correlating each interval in the choice sequence determining the argument with an interval in the choice sequence determining the value "interval by interval" as it were, the idea being that approximations to the input of the function should lead effectively to corresponding approximations to the input.
Binary collision approximation calculations provided input for the recoil energies due to MeV ions.
The architecture is designed to generate an output per clock cycle, and the detailed component and the approximation of the input signal are available alternately.
