A fractional scaling digital signal processing SDK, API, chipset integration, user-interface, and licensing platform utilizing sNRL's patented advanced mathematical algorithms based on fractional calculus further enhanced through and For deep learning and AI to filter, model, reconstruct, and synthesize digital signals from a variety of data measurements and sources such as audio, radio, video, industrial Sensors, SONAR, RADAR, and medical sensors.
Currently, one cannot just "Google" an algorithm for quick implementation. The sNRLTECH codebase provides a search engine for standardized algorithms and fractional order control system applications. Essentially, the API and SDK provide plug and play capability for sensors to use advanced digital signal processing combined with AI for rapid incorporation into prototypes and licensing of any proprietary algorithms. Although focused on Fractional Calculus and AI, the API and SDK may become a searchable database of proprietary algorithms. Scientists may add their own proprietary data or algorithms to the database and share in licensing fees as well creating a Clearinghouse for Algorithmic-based Tech. This would also create a market for algorithms at Universities that otherwise go unlicensed making them more accessible.
Once patented fractional calculus algorithms combined with AI are integrated into an API and SDK, sNRL's codebase may be deployed to run on many types of datasets or deployed via multiple types of microcontrollers or chipsets. Additionally, sNRL will be rolling out new applications as fields of use are identified, focusing on front-end/back-end design and maintenance within each specific field of use to ensure compatibility. sNRL anticipates that with feedback from our customers, additional feature sets, analysis, and use cases will continuously be developed and included in our data analytics pipeline.
The sNRLTECH API and SDK creates an architectural framework of modularized building block algorithms that seamlessly link together so that any signal is processed correctly with minimal effort. An import tool utilizing deep learning and AI would serve to orientate the input data correctly for the algorithms based on the type of data to be processed. Rapid generation of FSDSP filters are obtained through a Data Equalizer GUI. The entire fractional order control system may then be deployed on a microcontroller or sensor creating a pipeline of data flow, analysis, signal processing, and output to run IoT devices for Edge or Cloud computing.
Application Programming Interface (API)
Software Development Kit (SDK)
Fractional Scaling Digital Signal Processing (FSDSP) Chip/Microcontroller
sNRLTECH provides a Vehicle to License patented FSDSP technology enhanced with AI to a variety of industries and for use embedded in products automatically setting up licenses and billing according to use
Provides metrics of use and scaling so that licenses may be monitored and appropriately priced per data processed, field of use, and/or embedded product or FSDSP microcontroller or FSDSP Chipset
sNRL's API/SDK, containing our FSDSP Core Mathematics/AI Engine and Toolkits, lowers the bar of entry for anyone to use the power of fractional calculus combined with AI from the student to the advanced signals processing engineer, mathematician, or scientist (e.g., data equalizer)
Potential to also create dedicated user-based community in which scientists, engineers, and programmers may develop add-ons, specific front-ends for abstract data sets, or share data and settings driving engagement and licensing of sNRL technology