TLMM v4.3: Predictive Adaptive Control under Colored Noise — Extended Fokker–Planck Closure, Identifiability, Proof-of-Contact, and Translational Roadmap

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Autore principale: Okino, Koji
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2026
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author Okino, Koji
author_facet Okino, Koji
contents <p>This technical report presents TLMM v4.3, an exploratory mathematical framework for predictive adaptive control under colored noise. The work extends previous TLMM formulations by introducing an extended Fokker–Planck closure in <span class="katex"><span class="katex-mathml">(E,ξ)(E,\xi)</span><span class="katex-html"><span class="base"><span class="mopen">(</span><span class="mord mathnormal">E</span><span class="mpunct">,</span><span class="mord mathnormal">ξ</span><span class="mclose">)</span></span></span></span> space, theoretical operable-window narrowing, Kramers escape-based predictive maintenance timing, Fisher-information-based identifiability analysis, and an illustrative proof-of-contact with public CHB-MIT scalp EEG envelope statistics.</p> <p>The report also provides a translational roadmap toward future adaptive control architectures, while clearly distinguishing the current v4.3 position—qualitative proof-of-contact—from future development stages such as predictive benchmarking, closed-loop control, and adaptive digital models.</p> <p>This work is theoretical and exploratory. All EEG-related results are qualitative and illustrative only. No clinical, diagnostic, therapeutic, or medical-device claims are made.</p>
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spellingShingle TLMM v4.3: Predictive Adaptive Control under Colored Noise — Extended Fokker–Planck Closure, Identifiability, Proof-of-Contact, and Translational Roadmap
Okino, Koji
TLMM Predictive Adaptive Control Colored Noise Fokker–Planck Equation Kramers Escape Operable Window Predictive Maintenance Fisher Information Identifiability Analysis EEG Envelope Statistics CHB-MIT Ornstein–Uhlenbeck Process Stochastic Neural Field Adaptive Control Proof-of-Contact Translational Roadmap
<p>This technical report presents TLMM v4.3, an exploratory mathematical framework for predictive adaptive control under colored noise. The work extends previous TLMM formulations by introducing an extended Fokker–Planck closure in <span class="katex"><span class="katex-mathml">(E,ξ)(E,\xi)</span><span class="katex-html"><span class="base"><span class="mopen">(</span><span class="mord mathnormal">E</span><span class="mpunct">,</span><span class="mord mathnormal">ξ</span><span class="mclose">)</span></span></span></span> space, theoretical operable-window narrowing, Kramers escape-based predictive maintenance timing, Fisher-information-based identifiability analysis, and an illustrative proof-of-contact with public CHB-MIT scalp EEG envelope statistics.</p> <p>The report also provides a translational roadmap toward future adaptive control architectures, while clearly distinguishing the current v4.3 position—qualitative proof-of-contact—from future development stages such as predictive benchmarking, closed-loop control, and adaptive digital models.</p> <p>This work is theoretical and exploratory. All EEG-related results are qualitative and illustrative only. No clinical, diagnostic, therapeutic, or medical-device claims are made.</p>
title TLMM v4.3: Predictive Adaptive Control under Colored Noise — Extended Fokker–Planck Closure, Identifiability, Proof-of-Contact, and Translational Roadmap
topic TLMM Predictive Adaptive Control Colored Noise Fokker–Planck Equation Kramers Escape Operable Window Predictive Maintenance Fisher Information Identifiability Analysis EEG Envelope Statistics CHB-MIT Ornstein–Uhlenbeck Process Stochastic Neural Field Adaptive Control Proof-of-Contact Translational Roadmap
url https://doi.org/10.5281/zenodo.20122643