about
Detecting dynamical boundaries from kinematic data in biomechanicsDistinguishing time-delayed causal interactions using convergent cross mappingPredicting climate effects on Pacific sardineEfficient implementation of the gaussian kernel algorithm in estimating invariants and noise level from noisy time series dataLow-dimensional attractor for neural activity from local field potentials in optogenetic miceDon't bleach chaotic data.Noise in chaotic data: Diagnosis and treatment.Noise reduction in chaotic time-series data: A survey of common methods.Assessing the entropy changes of Bloch-vector trajectories using experimental data.Modeling dynamics from only output data.Generalized theorems for nonlinear state space reconstruction.Nonlinear time-series analysis revisited.Limits to Causal Inference with State-Space Reconstruction for Infectious Disease.Directed dynamical influence is more detectable with noise.Exploring techniques for vision based human activity recognition: methods, systems, and evaluationLocally embedded presages of global network bursts.Simple noise-reduction method based on nonlinear forecasting.As Good as GOLD: Gram-Schmidt Orthogonalization by Another Name.Prediction in projection.Information leverage in interconnected ecosystems: Overcoming the curse of dimensionality.Evaluation of an Expanded Disability Status Scale (EDSS) modeling strategy in multiple sclerosis.CauseMap: fast inference of causality from complex time series.Characterizing psychological dimensions in non-pathological subjects through autonomic nervous system dynamics.Control of chaos by random noise in a system of two coupled perturbed van der Pol oscillators modeling an electrical discharge plasma.Estimating the amplitude of measurement noise present in chaotic time series.Rhythms and complexity of respiration during sleep in pre-term infants.Sparse model from optimal nonuniform embedding of time series.Topological properties and fractal analysis of a recurrence network constructed from fractional Brownian motions.Optimal state-space reconstruction using derivatives on projected manifold.Observability of nonlinear dynamics: normalized results and a time-series approach.Estimating model parameters by chaos synchronization.Neural networks for estimating intrinsic dimension.Delay embedding in the presence of dynamical noiseAtmospheric Dynamics Leading to West European Summer Hot Temperatures Since 1851A new role for effort dynamics in the theory of harvested populations and data-poor stock assessmentNonlinear Dynamics of the Great Salt Lake: Dimension EstimationAn Information Criterion for Inferring Coupling of Distributed Dynamical SystemsModeling Nonlinear Dynamics and Chaos: A ReviewChaotic Patterns in Aeroelastic SignalsDetermining Neighborhoods of Image Pixels Automatically for Adaptive Image Denoising Using Nonlinear Time Series Analysis
P2860
Q28393333-C46AF816-F799-4A02-A2A0-301511954DD0Q28606945-644D70EA-F74E-44FD-B4D1-1F4462B38CA8Q30539047-B2E3DCAF-68C4-4771-821F-4DF8D1C41E21Q30620096-58283D62-75D6-45B0-853E-7AB0AE4895FFQ30666514-A6C5838F-32D7-4D8E-AE38-A5D2308FB348Q30799397-0184155C-F340-40AB-B1C9-06D29996E39FQ30799505-E649857C-AC4C-47E0-821D-193BD2E09AEAQ31912008-5273826B-128D-463A-8469-3427D6ABA0E5Q31924498-68DAF603-8E50-4B3C-9AF8-81A70D1B55D3Q33466321-F39003D3-5D5B-4240-9EA5-62D3ECF5D375Q33869792-1A325011-8B15-44A6-9159-A3193F52D416Q35795893-1C9F5814-F8EF-44EA-AEA6-8F13325DD4E9Q36234907-B50A8B39-7E57-43D5-87A1-629D683B9495Q36789750-EB216686-B331-49D8-984A-65A4F03E0924Q36830273-7399390C-9B8F-461D-AE9D-F73BB0B4B464Q38639195-444411A2-7DC8-47AD-A4F4-E7B318F18A8AQ38729554-E620A754-24CD-40B0-9E15-DD60E0FAC525Q38819300-C389B821-A0A0-4BD2-B11E-37D4E551E0A0Q38925512-5BB00D95-DBF5-423B-8A1B-035876A3890DQ39452079-611C568F-4C10-4F8C-8110-A6D1A9697E76Q40567136-215D2B16-95B3-463F-AFB5-BD77FC1FAC13Q41205070-C6B9393D-C61F-4461-9754-C56BF12762D9Q41901718-C7AE48BA-1E7C-4F2E-B5D7-122145A68CCDQ44145055-FCD12859-2A7D-4B81-BE7F-D3AED801EE13Q47869725-96521AE4-23C5-421C-9DAD-1D51DAB6ACB1Q48737661-274221A9-5E19-47A5-84CF-4FDB965D5A1EQ51086968-B05E85E7-89BB-4E75-BC54-608B9BAD0EB7Q51094224-B7816F6A-98CE-4DFC-B356-190906C09C3AQ51244929-894DE900-0FA2-4FD6-BD03-D18B42D043B5Q51889575-0228849F-4D6C-498F-B29C-74CAF2AD16FDQ51999305-AA1FAD31-C2F1-4696-A516-9525640BB226Q52040637-201DA6A6-9194-4571-9895-F05BF4F293F9Q57233210-76C139DB-2007-4E8F-BE85-6E530E37606FQ57886089-2CE28501-A399-4FBB-94C6-E7EABD5992D3Q58026765-77EAE3AF-3F76-40F1-AE67-63DF3C150E2FQ58092076-FDE19280-6D46-40D3-85E1-AAC7F2718C89Q58643739-9CFA81D3-5EA2-4D9B-B86C-FA4137E62285Q58648922-CB2FC3D9-48FD-4BB2-BED9-280F7B7AFC61Q58649503-944BE7EE-A1F8-4B95-BB21-49389B478B6DQ58653417-BC4F8514-C2B6-4AA4-8A29-C1970B600F55
P2860
description
article
@en
im August 1991 veröffentlicher wissenschaftlicher Artikel
@de
wetenschappelijk artikel
@nl
наукова стаття, опублікована в серпні 1991
@uk
ലേഖനം
@ml
name
State space reconstruction in the presence of noise
@en
State space reconstruction in the presence of noise
@nl
type
label
State space reconstruction in the presence of noise
@en
State space reconstruction in the presence of noise
@nl
prefLabel
State space reconstruction in the presence of noise
@en
State space reconstruction in the presence of noise
@nl
P2093
P1433
P1476
State space reconstruction in the presence of noise
@en
P2093
J.Doyne Farmer
John Gibson
Martin Casdagli
P356
10.1016/0167-2789(91)90222-U
P577
1991-08-01T00:00:00Z