Temporal Computer Organization
This addresses a limitation in biologically plausible neural network implementations, but it appears incremental as it builds on existing synchronization concepts.
The paper tackles the problem of functional completeness in temporally synchronized computing systems, particularly spiking neural networks, by proposing to use the synchronizing clock as an additional temporal reference input to remove restrictions.
This document is focused on computing systems implemented in technologies that communicate and compute with temporal transients. Although described in general terms, implementations of spiking neural networks are of primary interest. As background, an algebra for constructing temporal networks is summarized. Then, a system organization consisting of synchronized segments is described. The segments are feedforward internally with feedback between segments. A synchronizing clock resets network segments at the end of each computation step or cycle. In its basic form, the synchronizing clock merely performs a reset function. In the context of neural networks, this satisfies biological plausibility. However, functional completeness is restricted. This restriction is removed by allowing use of the synchronizing clock as an additional function input that acts as a temporal reference value.