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• W2745765378 abstract "A Hybrid Temporal Processing Element (HTPE) has been developed and implemented in VLSI circuitry. The HTPE closely models the spatio-temporal processing of biological neurons. Asynchronous spike-like action potentials (APs) robustly transmit data between neurons, which continuously convolve relatively slow time-varying post-synaptic potentials (PSPs) induced by impinging APs.The HTPE VLSI circuitry and model functionality have been refined over five generations of models. The present model is well suited for application to temporal signal processing problems. The resulting systems provide small, high-speed solutions to complex scientific and engineering problems.This dissertation is the cumulation of four years of research into the implementation of biologically-realistic neuron models in integrated electronics. The original contributions of this work include: (1) The HTPE is the first silicon-based model of the entire neuron; pre-synaptic region, post-synaptic region, dendritic tree, cell body (SOMA), axon hillock, axon, and collaterals. (2) The HTPE is the most biologically-realistic silicon-based neuron model, producing both APs and PSPs. The HTPE also maintains the continuous/asynchronous dynamics of biological neurons. (3) The custom VLSI circuitry of the HTPE has several unique features: (a) custom design and a novel design methodology have produced minimal sized circuits that operate at the maximal rate allowed by the particular VLSI process used for implementation, (b) external DC biases can be used to program the complete behavior of the HTPE, which allows for wide flexibility in system design, and (c) the HTPE CMOS devices are allowed to operate in all four modes of operation (cutoff, subthreshold, saturation, and ohmic), which allows the HTPE to process at speeds ranging from seconds to nanoseconds. (4) The DC biases that control the HTPE behavior can be modulated using hardware adaptation units that increment or decrement a bias voltage a small amount in response to input APs. The adaptation units provide an embedded hardware mechanism for network learning and programming. (5) Multi-HTPE systems have been developed for application to high-speed spatio-temporal signal processing problems. These systems are capable of processing on both the transient and steady-state components of their input signals. (6) The heuristic approach taken to HTPE system design requires a designer to have a knowledge of HTPE dynamics. This approach, however, has laid the foundation for the formation of a general-purpose methodology for HTPE system design." @default.
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• W2745765378 date "1992-01-01" @default.
• W2745765378 modified "2023-09-23" @default.
• W2745765378 title "Vlsi hybrid temporal neural networks for signal processing" @default.
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