Abstract: What does it mean to "train" a neural network? The network model we are using "learns" or gets better at its task by adjusting its connection strengths. We will strengthen those signals that tend to contribute to a right answer, and weaken those signals that tend toward a wrong answer. We do this by adjusting the potentiometer that lies in the path of each signal. It's kind of like changing the conductive environment in a neuron's synapse. To accomplish this, we will simply increase or decrease the voltage in question by 0.2V. That's our method of implementing back propagation of errors. Pretty crude, I know, but it makes for a good simulation of the process.
Publication Year: 2018
Publication Date: 2018-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 1
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