Spurious states detection and basin describing in feedforward neural networks

The problem of finding multilayer perceptron inputs belonging to “basins of attraction” of the outputs not from the learning set is concerned. A practical algorithm is proposed based on stochastic optimization. The algorithm performs the search of connected as well as disconnected parts of spurious attractor. The main advantage is that both parts of an algorithm don´t depend on the learning process