{"id":"W2368129884","doi":"","title":"Parameterization of Wavelet Transforms Based on CORDIC and Their Implemention","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CORDIC; Computer science; Wavelet; Fast wavelet transform; Rotation (mathematics); Orthogonal wavelet; Algorithm; Wavelet transform; Lifting scheme; Stationary wavelet transform; Orthonormality; Recursion (computer science); Discrete wavelet transform; Second-generation wavelet transform; Orthonormal basis; Field-programmable gate array; Artificial intelligence; Computer hardware","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008127391,0.0001340001,0.0001295388,0.0001035004,0.0001392815,0.00005308842,0.0003298153,0.00004061046,0.000002860383],"category_scores_gemma":[2.320927e-7,0.0001191627,0.00005758077,0.00040864,0.00004555692,0.0001409457,0.0000518995,0.00006049916,0.000004006216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002303975,"about_ca_system_score_gemma":0.00002524633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001606271,"about_ca_topic_score_gemma":0.000002603097,"domain_scores_codex":[0.9991007,0.00001749252,0.0003021838,0.0003389562,0.00009907455,0.0001416333],"domain_scores_gemma":[0.9993271,0.0001062086,0.0001252373,0.0003162162,0.00009023004,0.00003506554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004055039,0.0002762927,0.0001708345,0.00002924869,0.000007926516,1.575105e-7,0.00005346019,0.004072406,0.02351232,0.4443445,0.0005884849,0.5269403],"study_design_scores_gemma":[0.000839591,0.0002059168,0.009227918,0.00004794501,0.00001090698,0.00001311997,0.000008736395,0.4981091,0.06546357,0.220836,0.2047896,0.0004475988],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003064655,0.00002312655,0.9947376,0.0009357302,0.000004951185,0.0006831823,0.00003879114,0.0001790075,0.0003329906],"genre_scores_gemma":[0.4656842,0.000005385612,0.5335081,0.0003099724,0.00003230383,0.0003224885,0.0001194572,0.000007864252,0.00001018872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5264928,"threshold_uncertainty_score":0.4859314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005235607320820259,"score_gpt":0.2272754520893691,"score_spread":0.2220398447685488,"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."}}