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A weighted average is then taken off the weights between the shortlisted neighbors and the corresponding node of the link.
The collocation points and the relative weights between the residuals are derived from the weighted residual method.
The weights between the layers are adjusted according to the output layer error.
A more accurate and realistic representation of various scenarios involves certain weights between the associations.
The network is of functional nature as the weights between the hidden layer and the output are some polynomials.
Each individual consists of connection weights between the input layer and hidden layer, thresholds in the hidden layer, connection weights between the hidden layer and output layer, and the threshold in the output layer.
An adaptive fusion method is implemented by assigning different weights between the normalized contour and local feature maps.
The weights between the input and output layers can be adjusted to minimize the error between the input and output.
The weights between the hidden and output layers are determined in a one-step regression type approach using generalised inverse.
and therefore describe the connection weights between the neurons, and and represent the input of the neural network.
This paper proposes using PCR to obtain the weights between the hidden and output layers to overcome the multicollinearity problems.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com