Our patented Fractional Scaling Digital Filters or sNoise® Filters greatly improve upon the performance, accuracy, precision, and efficiency of current digital signal processing (DSP) filters, methods, and algorithms.
About sNoise Research Laboratory
The sNoise Research Laboratory (sNRL) is a research, development, and consultation service for enterprise businesses.Founded by Dr. Jeffrey Smigelski, sNRL is focused on the science of noise (sNoise®) and the corresponding technology applications using our patented Fractional Scaling Digital Signal Processing (FSDSP).
Information is all around us, but is often invisible, either not perceptible or lost in the noise. The science of noise, or sNoise® (registered trademark of sNoise Research Laboratory), can reveal information about recorded and measured quantities of real-world electrical or physical phenomenon which lead to technological advancements, better products, and a healthier and happier world.
As an innovator in the industry, sNoise Research Laboratory's mission is threefold:
- To bring focus and increase awareness to the science of Fractional Scaling Digital Signal Processing and the many potential applications leading to technological innovation and an improved quality of life.
- To provide tools and solutions that will reveal the hidden reality of information and the signal within the noise using more accurate and precise algorithms through our patented Fractional Scaling Digital Signal Processing methods and technologies.
- To partner with leading companies to create and improve products and services designed to advance the human condition through technological innovation.
The overall vision of the sNoise Research Laboratory (sNRL) is to provide our innovative Fractional Scaling Digital Signal Processing (FSDSP) algorithms as a go-to, foundational, platform technology for the digital age. sNRL can help you achieve revolutionary innovation through the application of sNoise® science and research to both current and new technologies within three key focus areas:
Including enhanced sensors, software algorithms, digital "smart" filters, chipsets, Fractional Order Control Systems, etc.
Focused on the conversion of existing and development of new technologies.
To discover and model the internal dynamics of natural or physical systems through a quantitative, equation-based approach using novel mathematical methods, computation experiments, and digital signal processing techniques to better understand and illuminate the world in which we live.