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| Main Author: | |
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| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2026
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.19309339 |
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Table of Contents:
- <div>To address the widespread lack of memory modulation mechanisms, the absence of closed</div> <div>loop design criteria, and insufficient engineering realizability in existing reaction-diffusion</div> <div>spatiotemporal computing systems, this paper proposes the third-generation Memory-Modulated</div> <div>Spatiotemporal Computing Model (MSCM 3.0). A minimally complete coupled partial dif</div> <div>ferential equation (PDE) system consisting of a signal field, a memory field, and an obstacle</div> <div>field is constructed. This work rigorously proves the necessary and sufficient conditions for</div> <div>the existence of propagation wavefronts, the criteria for convergence and non-convergence,</div> <div>the weak optimality of endogenous path selection, and the criteria for history dependence,</div> <div>thereby establishing a complete theoretical closed loop. Numerical experiments are designed</div> <div>to validate phase-diagram partitioning, wavefront propagation dynamics, and path formation</div> <div>mechanisms, and measurable engineering design indicators are provided. A benchmarking</div> <div>analysis is completed against classical reaction-diffusion systems, neural field models, and</div> <div>memristor networks, thereby clarifying the shared properties and core advantages of the pro</div> <div>posed model. By modulating the core control quantity—the effective growth rate µ(m, z)—</div> <div>MSCM 3.0 realizes programmable propagation-path design and completes the transition from</div> <div>a theoretical PDE system to an implementable spatiotemporal computing system, thus pro</div> <div>viding a new theoretical framework and implementation scheme for adaptive path planning,</div> <div>environmental perception, and related spatiotemporal computing tasks.</div>