Analog VLSI neural networks for impact signal processing

The architecture and operation of the 80170NX electrically trainable analog neural network, which recognizes objects in real time, are discussed. The 80170NX uses a discrete Fourier transform (DFT) to preprocess an accelerometer output waveform that is subsequently recognized through a multilayer perceptron neural network. It is shown that neural network hardware operating in a linear mode can perform conventional signal processing functions. The similarity of neural network computations to linear signal processing functions makes it exceedingly straightforward to integrate neural networks and conventional signal processing in the system.<>