Neural Network for lossless complex signal compression.
Thesis in external company
keywords ARTIFICIAL INTELLIGENCE, ARTIFICIAL NEURAL NETWORKS, DEEP NEURAL NETWORKS
Reference persons SANTA DI CATALDO, EDOARDO PATTI
External reference persons Alessandro Aliberti (firstname.lastname@example.org)
Research Groups DAUIN - GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ELECTRONIC DESIGN AUTOMATION - EDA, GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ICT4SS - ICT FOR SMART SOCIETIES
Thesis type EXPERIMENTAL
Description In signal processing, data compression, is the process of encoding information using fewer bits than the original representation. Lossless compression, in detail, reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. The modern development of machine learning techniques, in particular that of neural networks, allows the design of innovative and high-performance signal compression techniques.
This thesis aims at developing an innovative lossless compression technique of complex signal, by exploiting modern neural networks.
By addressing the problem of lossless compression, the student will analyze the literature solution to explore the state-of-art methodologies. Then, based on a compressed signal (i.e. ECG) the student will explore and design one (or more) neural network lossless compressor.
Required skills Python
Deadline 07/08/2023 PROPONI LA TUA CANDIDATURA