Pulse-Regulated Temporal Architecture for Persistent Cognitive Machines
Summary
The USPTO published patent application US20260094030A1 filed by Brian Galvin covering a pulse-regulated temporal architecture for persistent cognitive machines. The system implements adaptive curvature-based feedback across fast, medium, and slow pulse layers to maintain coherent timing in artificial cognition processes. The application was filed on December 8, 2025, with CPC classifications in G06N 5/04 and G06F 1/324.
What changed
Brian Galvin filed patent application US20260094030A1 for a pulse-regulated temporal architecture in persistent cognitive machines. The system maintains three pulse layers (fast, medium, slow) coupled through adaptive curvature-based feedback to sustain coherent timing. An elastic temporal manifold contracts during novelty and expands during stability, while spectral diagnostics monitor global order parameters to classify operating states including coherence, adaptation, and desynchronization. Automated controllers correct pathologies such as starvation, storm, and phase drift. In distributed configurations, multiple machines align intrinsic time geometries through curvature-diffusion coupling.
Patent applications do not impose compliance obligations on third parties. Technology companies and AI researchers may review the application to assess prior art or potential licensing considerations. The published application (No. 19412842) is available through the USPTO database. No deadlines or penalties are associated with this publication.
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Apr 3, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
Pulse-Regulated Temporal Architecture for Persistent Cognitive Machines with Curvature-Based Synchronization
Application US20260094030A1 Kind: A1 Apr 02, 2026
Inventors
Brian Galvin
Abstract
A system and method are provided for implementing a pulse-regulated temporal architecture in a multiscale persistent cognitive fabric. The system maintains fast, medium, and slow pulse layers coupled through adaptive curvature-based feedback to sustain coherent timing across cognitive processes. An elastic temporal manifold adjusts its internal rhythm in response to cognitive load, contracting during novelty and expanding during stability. Spectral diagnostics monitor a global order parameter and spectral entropy to classify operating states of coherence, adaptation, and desynchronization, while automated controllers correct pathologies such as starvation, storm, and phase drift. A closed feedback loop regulates temporal curvature through sensing, comparison, control, and actuation to maintain equilibrium. In distributed configurations, multiple persistent cognitive machines align their intrinsic time geometries through curvature-diffusion coupling across a shared communication manifold, achieving synchronized persistence and scalable, energy-efficient artificial cognition.
CPC Classifications
G06N 5/04 G06F 1/324 G06N 5/022
Filing Date
2025-12-08
Application No.
19412842
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