
TRNS (Temperature-Regularized Navier-Stokes) is a lightweight, training-free method for cleaning
sensor signals while preserving the features that matter.
No black box, no AI, no cloud required — just embedded physics that can be implemented with a software update.


About Us
Meadows McKnight LLC is a lean intellectual property company founded by husband-and-wife team Clinton and Jennifer Meadows. We develop and license TRNS through non-exclusive partnerships, focusing on practical solutions for real-world sensor systems. Based in East Texas, we take a straightforward, family-first approach to building and commercializing the technology.What is TRNS?
TRNS (Temperature-Regularized Navier-Stokes) is a physics-inspired signal processing operator designed to clean real-world sensor data. It applies structured stochastic damping derived from physical principles, with the goal of reducing noise while protecting the underlying shape and trends of the signal. It is tunable through a small set of parameters, requires no training data, and runs efficiently on edge and embedded hardware.No black box, no AI, no cloud required — just embedded physics that can be implemented with a software update.What makes TRNS unique?
Most existing approaches fall into two categories: classical filters or neural networks. TRNS sits outside both. It uses a physics-derived stochastic process and prioritizes structure preservation rather than maximum noise suppression. The same core method has shown consistent behavior across multiple physical domains — something uncommon for a single operator.So far, we have seen promising results in:
• Medical sensors (PPG, ECG, and related signals)
• Robotics and inertial measurement
• Aerospace and propulsion systems
• Speech and audio
• Industrial and equipment monitoring
• Data center coolingThe operator is also bidirectional. In one direction it functions as a denoising method; in the other it can operate in a forward generative mode for structured signal modeling.Headquarters
Kilgore, Texas. Founded 2026Intellectual Property & Licensing
TRNS technology is protected by a pending U.S. patent. Meadows McKnight LLC offers non-exclusive licensing opportunities to qualified partners. All technical details, algorithms, and implementation methods remain the proprietary and confidential property of Meadows McKnight LLC. Unauthorized use, reproduction, or distribution is prohibited.

Demos
Medical & Wearables
Robotics / Drones
Aerospace & Propulsion
- NASA CMAPSS FD004 Turbofan Engine Sensor Denoising
- NASA Li-Ion Battery Capacity Fade Denoising
- LIGO - Gravitational Wave Signal Denoising
Speech & Audio
Industrial and Equipment Monitoring
- Battery Capacity Denoising - Progressive (Streaming)
- Materials (Oscilloscope)
- Bearing Vibration Denoising
Data Center Cooling

Articles & News
- When Cleaning a UWB Signal Makes Ranging Worse - 8/12/2026
- Why Cleaner Signals Beat Bigger Models - 8/10/2026
- TRNS Progressive (Streaming) Operator for Battery Capacity Denoising Causal Results on the Oxford Battery Degradation Dataset - 8/2/2026
- When “Do Nothing” Beats Denoising: Lessons from Bearing Vibration - 7/29/2026
- One Algorithm, Many Sensors: Rethinking Denoising on Drones and Robots - 7/28/2026
- From Offline Experiment to Streaming Pre-Denoiser: Making TRNS Work in Real Time on Fan Noise - 7/24/2026
- What TRNS Has Taught Me About Signal Value Across Domains - 7/22/2026
- Physics Does Not Hallucinate - 7/21/2026
- Extending TRNS into New Domains: Early Experiments on Speech Denoising - 7/20/2026
- Why Removing the Most Noise Isn’t Always the Right Goal - 7/17/2026
- Why TRNS Beats Traditional Filters for Real-World Medical & Aerospace Sensors - 7/15/2026
- Why Edge Fit Matters More Than Raw Performance in Medical Wearables - 7/13/2026
- TRNS: A Lightweight, Training-Free Approach for Motion Artifact Removal in Wearable PPG - 7/8/2026
- Post: Meadows McKnight - Seeking Collaborators for Field Testing & Real-World Pilots - 7/7/2026
- TRNS: A Lightweight Physics-Based Approach for Denoising Arterial Signals in Vascular Digital Twins - 7/4/2026
- Better EMG Denoising for Wearables & Prosthetics — Without the Heavy Compute - 7/1/2026
- TRNS on NASA Battery Data: Preserving Degradation Trends for Accurate State-of-Health Estimation - 6/29/2026
- TRNS Stochastic Damping for Edge Devices: Physics-Based Denoising Preserves Spikes on Real Pediatric Epilepsy EEG Data - 6/27/2026
- The Art and Science of Tuning TRNS: Why Blindly Chasing RMS Reduction Can Hurt Real-World Performance - 6/27/2026
- ECG Denoising for Wearables: A Lightweight, Training-Free Physics-Based Approach - 6/26/2026

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