Uncertainty analysis is often called the " propagation of error ."
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This propagation of errors is indicated by the blue color in the graphical description.
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The feedback provided by the backward propagation of errors would be used to improve accuracy for the network s subsequent responses.
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A more elegant way of writing the so-called " propagation of error " variance equation is to use matrices.
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This extra flexibility can improve compression efficiency, but it can cause propagation of errors if some data becomes lost or corrupted.
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Multilayer Perceptron ( MLP ) is the most popular of all the types, which is generally trained with back-propagation of error algorithm.
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Hierarchical B pictures can provide very good compression efficiency and can also limit the propagation of errors, since the hierarchy can ensure that the number of pictures affected by any data corruption problem is strictly limited.
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In statistics, "'propagation of uncertainty "'( or "'propagation of error "') is the effect of precision ) which propagate to the combination of variables in the function.
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"' The backward propagation of errors "'or "'backpropagation "', is a common method of training artificial neural networks and used in conjunction with an optimization method such as gradient descent.
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One popular approach for approximating the weights so the error term is minimized is with a learning algorithm called the generalized delta rule that is incorporated in a training procedure called "'back propagation of error " '.
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