Controlling basins of attraction in a neural network-based telemetry monitor
Benjamin Bell, James L. Eilbert · NASA Technical Reports Server (NASA) · 1988
The size of the basins of attraction around fixed points in recurrent neural nets (NNs) can be modified by a training process. Controlling these attractive regions by presenting training data with various amount of noise added to the prototype signal vectors is discussed. Application of this technique to signal processing results in a classification system whose sensitivity can be controlled. This new technique is applied to the classification of temporal sequences in telemetry data.