Reduced Interference Sparse Time-Frequency Distributions for Compressed Observations PROJECT TITLE :Reduced Interference Sparse Time-Frequency Distributions for Compressed ObservationsABSTRACT:Traditional quadratic time-frequency distributions are not designed to deal with randomly undersampled signals or knowledge with missing samples. The compressed knowledge measurements introduce noise-like artifacts in the ambiguity domain, compounding the matter of separating the signal auto-terms and cross-terms. During this paper, we tend to propose a multi-task kernel design for suppressing each the artifacts and therefore the cross-terms, while preserving the signal desirable auto-terms. The proposed approach results in highly focused time-frequency signature. We evaluate our approach using various polynomial part signals and show its advantages, particularly within the case of sturdy artifacts. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Bayesian Estimation in the Presence of Deterministic Nuisance Parameters—Part II: Estimation Methods Fronthaul and backhaul requirements of flexibly centralized radio access networks
