Parma, Italy

Martino Ferrari


 

Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2021

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1 patent (USPTO):Explore Patents

Title: Martino Ferrari: Innovator in Signal Processing

Introduction

Martino Ferrari is a notable inventor based in Parma, Italy. He has made significant contributions to the field of signal processing, particularly through his innovative patent. His work focuses on enhancing the methods of sampling and decoding signals, which has implications in various technological applications.

Latest Patents

Martino Ferrari holds a patent titled "Signal sampling with joint training of learnable priors for sampling operator and decoder." This patent describes a method of sampling and decoding a signal of interest, which involves a training stage and a sampling stage. During the training stage, a set of training signals is acquired, and a sampling operator and decoder are provided. The operator is trained on these signals to obtain a learned sampling operator. In the sampling stage, the learned operator is applied to the signal, resulting in an observation signal. The decoder is then used to produce an estimate of the original signal, showcasing a sophisticated approach to signal processing.

Career Highlights

Martino Ferrari is affiliated with the University of Geneva, where he continues to advance his research in signal processing. His academic background and ongoing projects contribute to the development of innovative technologies in this field.

Collaborations

Some of his notable coworkers include Sviatoslav Voloshynovskiy and Olga Taran, who collaborate with him on various research initiatives. Their combined expertise enhances the quality and impact of their work in signal processing.

Conclusion

Martino Ferrari's contributions to signal processing through his innovative patent demonstrate his commitment to advancing technology in this area. His work not only reflects his expertise but also has the potential to influence future developments in signal processing.

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