Abstract
Today, big data is either unavailable or expensive. But it is necessary to investigate the behavior of neural networks of direct propagation right now. That is why it is necessary to model arrays of data (samples) with specified properties (for example, arrays of correlated quantities of any finite dimension) in order to investigate the behavior of neural networks of direct propagation of any architecture. It is possible to implement the task of forming such samples using the Monte Carlo method.
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