Second order dimensionality reduction using minimum and maximum mutual information models

PLoS Computational Biology

Volumn 7, Issue 10, 2011, Pages

  Fitzgerald, Jeffrey D ^a,b   Rowekamp, Ryan J ^a,b   Sincich, Lawrence C ^c   Sharpee, Tatyana O ^a,b  

^a SALK INSTITUTE FOR BIOLOGICAL STUDIES   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN NOISE (ELECTRONIC);

CONVENTIONAL METHODS; CURSE OF DIMENSIONALITY; DIMENSIONALITY REDUCTION; FEATURE SELECTIVITY; GAUSSIANS; MAXIMUM MUTUAL INFORMATION; MINIMUM MUTUAL INFORMATIONS; MUTUAL INFORMATION MODELS; NON-GAUSSIAN; SECOND ORDERS;

GAUSSIAN DISTRIBUTION;

ANALYTIC METHOD; ANIMAL CELL; ARTICLE; CELL ASSAY; CELL SELECTION; CONTROLLED STUDY; INTERMETHOD COMPARISON; LINEAR SYSTEM; MATHEMATICAL MODEL; NERVE CELL NETWORK; NERVE CELL STIMULATION; NONHUMAN; PROCESS MODEL; RETINA GANGLION CELL; RHESUS MONKEY; SPIKE; SPIKE TRIGGERED COVARIANCE; STATISTICAL DISTRIBUTION; STIMULUS RESPONSE; ACTION POTENTIAL; ALGORITHM; ANIMAL; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENICULATE BODY; MACACA; PHYSIOLOGY;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; COMPUTER SIMULATION; GENICULATE BODIES; MACACA; MODELS, NEUROLOGICAL; RETINAL GANGLION CELLS;

EID: 80055086683     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002249     Document Type: Article

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