Company Filing History:
1 out of 832,761 Years Active: 2004
**Title: Innovations in Signal Processing: The Work of Stéphane Mallat**
Introduction
Stéphane Mallat, a distinguished inventor based in Paris, France, has made significant contributions to the field of signal processing. With a strong focus on developing methods for processing and compressing n-dimensional signals, his work stands at the intersection of mathematics and technology.
Latest Patents
Mallat holds a patent for a "Method and apparatus for processing or compressing n-dimensional signals by foveal filtering along trajectories." This innovative patent encompasses methods and apparatus designed to handle n-dimensional digitized signals through foveal processing. His invention enables the construction of a sparse representation by utilizing the geometrical regularity inherent in signal structures. The patented technology can compress, restore, match, and classify signals efficiently.
Career Highlights
Mallat's patented method computes foveal coefficients using one-dimensional inner products along specific trajectories of an n-directional trajectory list. An essential component of his invention is a trajectory finder that computes this list from the input n-dimensional signal to select optimal locations for foveal coefficient calculations. Furthermore, his foveal reconstruction processor is capable of recovering a signal approximation retaining the geometrical structures of the original signal along these trajectories, while also ensuring regularity away from them.
Collaborations
Stéphane Mallat collaborates with his coworker, Erwan Le Pennec, in advancing research and practical applications of his invention. Their partnership enhances the development of technologies focused on efficient signal processing techniques.
Conclusion
Through his innovative work and dedication to exploring advanced methodologies in signal processing, Stéphane Mallat exemplifies the impact inventors can have across various technology sectors. His patent not only reflects his ingenuity but also demonstrates the potential for practical applications in data handling and analysis. The advancements stemming from his research are likely to influence future developments in the field.