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Intel CSI Tool vs Nexmon for Neural RF Sensing

We present a controlled bake-off betweentwo widely used Wi-Fi CSI capture stacks—the IntelCSI Tool and Nexmon—for neural RF sensing. Wecompare subcarrier resolution, signal stability, andsetup cost, and offer platform guidance grounded inreproducible scripts and auto-press… 

CSI→Voxel: Wi-Fi Sensing as a Low-Cost fMRI Proxy

Functional magnetic resonance imaging (fMRI) provideshigh-resolution, voxel-wise measurements of brain activity, butacquiring large-scale fMRI datasets is expensive, immobile,and time-consuming. At the same time, commodity wirelessdevices continually capture channel state information (CSI)— a rich, multi-dimensional signal… 

RL-Driven RF Neuromodulation

🧠 Reinforcement Learning Takes the Wheel: A Smarter Approach to RF Neuromodulation Neuromodulation—using techniques like radiofrequency (RF) energy to precisely tune brain activity—holds immense promise for treating neurological conditions. However, achieving effective and safe closed-loop… 

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… 

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… 

DOMA-Based RF Motion Tracking and Trajectory Forecasting

We integrate a DOMA motion head into an RFtracking stack to forecast next-position and short-horizon trajectories from spectral/angle features. A variance-aware fusionwith a kinematic filter yields stable paths under SNR variation.We document latency, accuracy, and… 

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:…