Several research groups are implementing analog integrated circuit models of biological auditory processing. The outputs of these circuit models have taken several forms, including video format for monitor display, simple scanned output for oscilloscope display, and parallel analog outputs suitable for data-acquisition systems. Here, an alternative output method for silicon auditory models, suitable for direct interface to digital computers, is described. As a prototype of this method, an integrated circuit model of temporal adaptation in the auditory nerve that functions as a peripheral to a workstation running Unix is described. Data from a working hybrid system that includes the auditory model, a digital interface, and asynchronous software are given. This system produces a real-time X-window display of the response of the auditory nerve model.

An approach to solving the two most serious shortcomings of previous artificial neural network implementations is discussed. A flexible architecture that permits the realization of arbitrary network topologies and dimensions is presented. Furthermore, the performance of this architecture is independent of the size of the network and permits the processing of typically 100000 patterns per second. The key innovation is the representation of neuron activations and synaptic weights as stochastic functions of time, leading to efficient implementations of the synapses. High densities of synapses per silicon area, exceeding even analog implementations, have been achieved. Finally, the neuron activations are represented digitally, as are the synaptic computations, thereby permitting fabrication of digital neural network architectures using a variety of standard, low-cost semiconductor processes. A pair of general-purpose chips (SU3232 and NU32) that permit post facto construction of neural networks of arbitrary topology and virtually unlimited dimensions is presented