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Multi-Role Ground Nodes as Command Relays: Reliability Anchors and Fan-Out Hubs for Routing and RF Processing

Hub Failure Scenarios for Multi-Role Ground Nodes as Command Relays Assessing Resilience and Graceful Degradation in Contested RF Control Planes By Benjamin J. GilbertExperimental Solutions Implementationbgilbert2@com.eduFull Paper PDF · Reproducible Code (coming soon)Published: October 29,… Multi-Role Ground Nodes as Command Relays: Reliability Anchors and Fan-Out Hubs for Routing and RF Processing

FFT-Only Spectral Triage for Low-Latency RF Control Planes: From 1.5 ms Digital-vs-Analog Decisions to Near-100% Command Success

Spectral triage in contested environments faces the dual challenge of rapid classification and reliable subsequent operations.FFT-based feature extraction provides deterministic latencyand interpretable spectral characteristics, making it suitablefor real-time systems where compute budgets are constrained.However, pure… FFT-Only Spectral Triage for Low-Latency RF Control Planes: From 1.5 ms Digital-vs-Analog Decisions to Near-100% Command Success

Multi-Band Trade-offs: 2.4 GHz vs 5.8 GHz vs mmWave vs sub-GHz Depth vs Resolution vs Safety with Controller Robustness

Real-World Examples of RF Neuromodulation Systems This Spectrcyde paper provides an excellent physics-based framework for multi-band RF neuromodulation trade-offs, but as noted in my previous critique, it relies on simplified models without grounding in empirical… Multi-Band Trade-offs: 2.4 GHz vs 5.8 GHz vs mmWave vs sub-GHz Depth vs Resolution vs Safety with Controller Robustness

Safety Budgets for RF Neuromodulation: Closed-Loop Power Minimization with Reinforcement Learning

Xinhao Liandao Radio-frequency neuromodulation has emerged as a promising therapeutic modality for treating neurological disorders,offering precise spatial targeting and non-invasive delivery [1].However, RF energy deposition in biological tissues raisescritical safety concerns, particularly regarding specific absorption… Safety Budgets for RF Neuromodulation: Closed-Loop Power Minimization with Reinforcement Learning

QuestDB + CrateDB as Dual-Store Telemetry Backbone: Performance Benchmarking and Cost Analysis

Modern distributed systems generate massive volumes oftelemetry data requiring both real-time processing and longterm analytical storage. Traditional single-database approachesstruggle to optimize for conflicting requirements: time-seriesworkloads demand high ingestion throughput and temporalqueries, while analytical workloads require… QuestDB + CrateDB as Dual-Store Telemetry Backbone: Performance Benchmarking and Cost Analysis

Multi-Source Context Fusion for SIGINT: Marrying SDR Streams with Astrophysical (JWST), Orbital (ISS), and HEP (LHC) Telemetry to Enrich Classification

We study multi-source context fusion for signal classification from software-defined radio (SDR) streams. We exploreenriching SDR features with contemporaneous, public-domaintelemetry from astrophysical (e.g., observatory scheduling andenvironment), orbital (e.g., satellite attitude/visibility windows),and high-energy physics (e.g., collider… Multi-Source Context Fusion for SIGINT: Marrying SDR Streams with Astrophysical (JWST), Orbital (ISS), and HEP (LHC) Telemetry to Enrich Classification

My Shit List

Davie Jonez 19 mutual friends Catherine Bradford 16 mutual friends Matthew Gilbert 5 mutual friends Melissa Williams 32 mutual friends Ann Fassetta 18 mutual friends Rick Heinicken 2 mutual friends Vincent Gilbert 7 mutual friends… My Shit List

Atmospheric Propagation & Ringdown Modes for RF “Ghosts”: A Minimal FastAPI and Reference Implementation

The RK4 (Runge-Kutta 4th order) integration method is a numerical technique used in your paper’s atmospheric ray tracing component (/v1/propagate) to solve the differential equations governing RF signal propagation paths in a modified-refractivity profile (z,… Atmospheric Propagation & Ringdown Modes for RF “Ghosts”: A Minimal FastAPI and Reference Implementation

Latent Attention

Latent Attention is an innovative approach designed to optimize the efficiency of attention mechanisms in transformer models, particularly for RF (Radio Frequency) spectrum modeling as explored in the paper Normalization & Attention Backends for RF:… Latent Attention

Normalization & Attention Backends for RF: RMSNorm + AttentionModelAdapter comparing FlashMHA, Grouped, Latent, and Baseline MHA

Blog Post: Exploring Normalization and Attention Backends for RF with RMSNorm and AttentionModelAdapter Introduction Welcome to our deep dive into the latest advancements in RF (Radio Frequency) spectrum modeling! In a recent study titled Normalization… Normalization & Attention Backends for RF: RMSNorm + AttentionModelAdapter comparing FlashMHA, Grouped, Latent, and Baseline MHA