Pipelined analog multi-layer feedforward neural networks

Two methods for pipelining analog or hybrid neural networks with analog outputs are presented. These methods provide concurrent operation of various stages on different sets of the network input stream. A new analog neuron with an embedded latch for implementation of one of the architectures is also presented. These methods are particularly attractive for time-multiplexed implementation of multi-layer neural networks. It is shown that significant speed improvement can be achieved by these methods