backpropagation

Noun

Meaning

(computing) An error correction technique used in neural networks

(neurology) A phenomenon in which the action potential of a neuron creates a voltage spike both at the end of the axon, as normally, and also back through to the dendrites from which much of the original input current originated.

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Examples

Backpropagation and resurgence A key advance that came later was the backpropagation algorithm which effectively solved the exclusive-or problem, and more generally the problem of quickly training multi-layer neural networks (Werbos 1975). Source: Internet

They are stacks of information-transforming modules that “learn” by repeatedly computing a chain of what are known as gradients (something rarely taught in high school calculus), which are the backbone of a family of algorithms known as backpropagation. Source: Internet

Generalization of backpropagation with application to a recurrent gas market model. Source: Internet

Unlike traditional artificial neural networks, spiking neural networks don’t require neurons to fire in each backpropagation cycle of the algorithm, but, rather, only when what’s known as a neuron’s “membrane potential” crosses a specific threshold. Source: Internet

I have a question on the backpropagation in a simple neural network (I am trying to derive the derivative for the backpropagation). Source: Internet

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