Field
Certain aspects of the present disclosure generally relate to neural system engineering and, more particularly, to systems and methods for monitoring a neural network with a shadow network.
Background
An artificial neural network, which may comprise an interconnected group of artificial neurons (i.e., neuron models), is a computational device or represents a method to be performed by a computational device. Artificial neural networks may have corresponding structure and/or function in biological neural networks. In some cases, artificial neural networks may provide innovative and useful computational techniques for certain applications in which traditional computational techniques are cumbersome, impractical, or inadequate. Because artificial neural networks can infer a function from observations, such networks are particularly useful in applications where the complexity of the task or data makes the design of the function by conventional techniques burdensome. Still, like most systems, the neural networks may fail or become unstable. Thus, it is desirable to provide a neuromorphic receiver that includes a shadow neural network for monitoring the activity of a target neural network. The shadow neural network may improve the debugging and/or monitoring of the target neural network.