Scaled correlation analysis: a better way to compute a cross-correlogram.
about
Confidence Leak in Perceptual Decision MakingMethod for stationarity-segmentation of spike train data with application to the Pearson cross-correlation.Distinct behavioural and network correlates of two interneuron types in prefrontal cortex.A robust cell counting approach based on a normalized 2D cross-correlation scheme for in-line holographic images.Dually fluorescent core-shell microgels for ratiometric imaging in live antigen-presenting cellsAnalysis of the Influence of Hormone Replacement Therapy on Osteocalcin Gene Expression in Postmenopausal Women.Structure, Function, and Propagation of Information across Living Two, Four, and Eight Node Degree Topologies.Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods.Optimization of a cell counting algorithm for mobile point-of-care testing platforms.Prognostic importance of lymph node-to-primary tumor standardized uptake value ratio in invasive squamous cell carcinoma of uterine cervix.How do online social networks grow?Tracking single units in chronic, large scale, neural recordings for brain machine interface applications.Synchronisation hubs in the visual cortex may arise from strong rhythmic inhibition during gamma oscillations.Novel perspective on field recordings in zebrafish models of epilepsy.Differential alterations of resting-state functional connectivity in generalized anxiety disorder and panic disorder.A Bayesian measure of association that utilizes the underlying distributions of noise and informationSmoothing the Sample Autocorrelation of Long-Range-Dependent Traffic
P2860
Q28607685-24E39F39-E3D5-4B4E-9F81-7182A1B7BA24Q30620796-D260BA27-F82E-4548-ABBE-93752BA90AD1Q30624577-2F7C7B06-DF4F-4D9F-9C38-919E5C42BDFDQ34803954-E76769BD-6A46-40BE-A0A1-3B7FDC6497ECQ35088571-372CF52F-AC31-4FBE-914D-15ACC5AAC4A2Q36017447-243B01B4-39AC-4C02-AA03-A39113E8FE12Q36627845-5E755E10-4BCB-4EB2-8575-CC9AFCEAC0ABQ37402632-25AC80A1-7BAB-4396-9073-CA77954446CCQ38434376-55CE79F7-8566-4B1A-990B-3D0423AF9F08Q38769655-AD032A8F-9766-47BE-ADC8-5A32E3E63AF7Q40857038-27E5B7FF-0537-4273-8F0B-57D5002E2177Q42724814-57413843-DE9A-4907-8CD2-FA8418C1FE38Q46314367-9F4F68D3-552D-4C66-B9E2-55C574ED77DAQ46456653-0A6EAD16-4CFE-4809-A6D1-FC2C954F9542Q48955073-D642ECF4-97AA-40B3-A09D-14FEBBF8D3C6Q58771735-C076DB2F-9718-40C4-8F56-54436635FD59Q59031120-B5681BC5-80AA-4244-88A7-5A15C69BC081
P2860
Scaled correlation analysis: a better way to compute a cross-correlogram.
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
@zh-hant
name
Scaled correlation analysis: a better way to compute a cross-correlogram.
@en
Scaled correlation analysis: a better way to compute a cross-correlogram.
@nl
type
label
Scaled correlation analysis: a better way to compute a cross-correlogram.
@en
Scaled correlation analysis: a better way to compute a cross-correlogram.
@nl
prefLabel
Scaled correlation analysis: a better way to compute a cross-correlogram.
@en
Scaled correlation analysis: a better way to compute a cross-correlogram.
@nl
P2093
P2860
P1476
Scaled correlation analysis: a better way to compute a cross-correlogram.
@en
P2093
Raul C Mureşan
Weijia Feng
Wolf Singer
P2860
P304
P356
10.1111/J.1460-9568.2011.07987.X
P407
P577
2012-02-13T00:00:00Z