The Rosetta Wheel™ Framework is an independent research framework developed by Ashley Iannetti through Iannetti Studies. It explores whether structural relationships within complex systems can be compared through normalization and shared reference mapping.
Normalized Frequency Space (NFS) is the analytical method used within the framework to transform signals into a common mathematical space, allowing structural relationships to be explored independently of their original scale.
Originally developed through bioacoustic research, NFS has since been preliminarily explored across additional signal domains, including physiological, neural, and engineering datasets.
Signals are often studied in isolation because they exist on vastly different scales. Animal vocalizations, ECG recordings, neural activity, machine vibrations, and engineering sensor systems frequently require separate analytical approaches.
This can make direct comparison difficult and may obscure structural patterns that could exist across different systems.
The NFS approach focuses on structural relationships within signals rather than scale alone, creating a shared reference space for exploratory analysis, applied testing, and further evaluation.
Structural signal analysis was applied to the NASA CMAPSS turbofan degradation dataset to investigate whether structural behavior could provide complementary insight alongside RMS-based approaches.
In preliminary internal testing, the method showed early instability behavior in multiple engines and improved consistency when combined with RMS-based analysis.
These results are not presented as NASA validation, endorsement, or independent confirmation. They are shared as preliminary dataset testing to support further review, replication, and applied evaluation.
I am currently interested in connecting with researchers, engineers, AI and machine learning teams, universities, industry partners, and organizations working with complex signal datasets.
Areas of interest include:
Ashley Iannetti
Independent Researcher
Iannetti Studies
For research collaborations, consulting inquiries, speaking opportunities, applied testing projects, or signal-analysis discussions, please reach out: