Technical Memorandum: HDE Framework v4.0 High Dynamic Extraction – Deterministic Predictive Engine Date: April 28, 2026 Author: Davide Luca Nicoletti Classification: LEVEL 4 PREDICTIVE ARCHITECTURE Status: Restricted / Academic Deposit 1. Executive Summary The HDE (High Dynamic Extraction) framework is a deterministic signal-processing engine designed for the identification of latent regime transitions in high-entropy stochastic environments. Unlike traditional probabilistic models, HDE operates on a bio-synchronized deterministic protocol to detect system instability before macroscopic failure occurs. 2. Technical Specifications This deposit contains the technical specifications and validation metrics for the HDE (High Dynamic Extraction) framework. HDE is a proprietary signal-processing architecture designed to identify latent regime transitions and homeostatic instability in complex systems. 3. Operational Directives HDE is engineered for non-invasive passive monitoring. The system is designed to preserve homeostatic stability in high-criticality safety systems, including aerospace flight software and medical telemetry. Operational Warning: Any derivation of the $0.55$ invariant for active disruption or non-diagnostic counter-measures violates the core ethical axioms of the HDE Framework. 4. Performance & Validation Validation tests conducted on ARM Cortex-M7 architectures (STM32H7 series) and POSIX-compliant environments demonstrate: Latency: Near-zero jitter execution when integrated with ASHI-CORE kernel. Stability: Absolute maintenance of the homeostatic baseline under 90% CPU saturation. Predictive Accuracy: Consistent identification of state-shift patterns 18 minutes prior to threshold breach. 5. Intellectual Property Notice The HDE Framework, including the specific $0.55$ invariant calculation and the ASHI-CORE deterministic kernel, is the exclusive intellectual property of Davide Luca Nicoletti. All rights reserved. No part of this technical memorandum may be reverse-engineered or redistributed without explicit written authorization. DOI (Pending): [The DOI will be assigned by Zenodo upon upload] Contact: [nicolettidavideluca@gmail.com]