| KEYWORD |
Signal Processing and Image Classification via Bio-inspired Hopfield-based Associative Networks
keywords CLASSIFICATION ALGORITHMS, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS
Reference persons IGOR SIMONE STIEVANO, RICCARDO TRINCHERO
Research Groups EMC Group (Electromagnetic Compatibility)
Thesis type II LEVEL DEGREE, RESEARCH ORIENTED, RESEARCH, INNOVATIVE
Description The proposed research activity focuses on the study, development and application of a machine learning technique to signal processing (e.g., noise reduction) and to classification problems. An Hopfield-based bio-inspired associative network is considered. Matlab and/or Python will be used for the implementation of routines.
Required skills Matlab, Python and basics of modeling and simulation.
Deadline 17/06/2023
PROPONI LA TUA CANDIDATURA