Hybrid Analog Signal-Based Models of Computation

TL;DR

This paper reviews and proposes hybrid analog signal-based models of computation, integrating signal processing, computational theory, and physical processes to enable novel, distributed, and autonomous computational systems with potential applications in multi-agent systems.

Contribution

It introduces new hybrid analog models merging signal processing with computational theory, exploring physical foundations and applications in distributed and autonomous systems.

Findings

Proposes analog signal-based computational models.

Suggests transforming RF networks into holographic computational media.

Examines applications in multi-agent systems.

Abstract

The present work attempts both a review of previous methods for transferring digital and symbolic computations in an analog or optical substrate and also to offer certain alternatives not yet fully explored. The essential difference from previous cases lies in the merging of general signal processing and computational theory with some emphasis on the foundations of computations and its logico-mathematical background and possible connections with fundamental physical processes. The technologies proposed could among other things be used to turn a standard RF network into a complete, autonomous holographic or distributed computational medium. Some applications for Multi-Agent Systems are also examined near the end.