In most cases, the output weights of hidden nodes are usually learned in a single step, which essentially amounts to learning a linear model. they are random projection but with nonlinear transforms), or can be inherited from their ancestors without being changed. These hidden nodes can be randomly assigned and never updated (i.e.
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