Reconstruction of Non-stationary Signals with Missing Samples using Time-frequency Filtering Workshop

On February 21st, 2021 college of Engineering and Computer Science conducted a workshop presented by lecturer Mokhtar Mohammed at 10:00 am in room 3008 under the title “Reconstruction of Non-stationary Signals with Missing Samples using Time-frequency Filtering Workshop”, 16 participants from ECS attended the workshop. The content of the workshop was : This study proposes a new Time-frequency (TF) method for recovery of missing samples from multi-component signals. This is achieved by a combination of a sparsity aware TF signal analysis method with TF littering technique. A sparsity aware TF method overcome distortions caused by missing samples in the TF domain. This is followed by use of TF littering techniques for recovery of signals. All the extracted components are then combined
to recover the complete signal. The proposed method outperforms other signal recovery methods such as gradient descent algorithm and Matching pursuit
(MP).

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