{"id":"W2145487065","doi":"10.1016/j.dsp.2007.12.004","title":"Time–frequency feature representation using energy concentration: An overview of recent advances","year":2008,"lang":"en","type":"article","venue":"Digital Signal Processing","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":746,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Feature (linguistics); Computer science; Signal processing; Frequency domain; Energy (signal processing); SIGNAL (programming language); Time–frequency analysis; Representation (politics); Artificial intelligence; Time domain; Domain (mathematical analysis); Pattern recognition (psychology); Machine learning; Data mining; Digital signal processing; Mathematics; Statistics; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06821636393239666,"score_gpt":0.2987034494592146,"score_spread":0.230487085526818,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}