Computational principles underlying the recognition of acoustic signals in insects

Journal of Computational Neuroscience

Volumn 35, Issue 1, 2013, Pages 75-85

  Clemens, Jan ^a,b,c   Hennig, R Matthias ^a  

^a HUMBOLDT UNIVERSITY   (Germany)

^b BERNSTEIN CENTER FOR COMPUTATIONAL NEUROSCIENCE   (Germany)

^c PRINCETON UNIVERSITY   (United States)

Author keywords

Gabor filter; Insect; Linear nonlinear model; Perceptual decision making; Song

Indexed keywords

BANDPASS FILTERS; DECISION MAKING; FEATURE EXTRACTION; GABOR FILTERS; PHYSIOLOGICAL MODELS; PHYSIOLOGY;

ACOUSTIC COMMUNICATIONS; ACOUSTIC SIGNALS; INSECT; LINEAR-NONLINEAR MODELS; PERCEPTUAL DECISION MAKING; PREFERENCE FUNCTIONS; PULSE-LIKE; SIMPLE++; SONG; TWO TIME SCALE;

ANIMALS;

ALGORITHM; ANIMAL BEHAVIOR; ARTICLE; AUDITORY DISCRIMINATION; AUDITORY FEEDBACK; AUDITORY RESPONSE; COCHLEAR NERVE; CONTROLLED STUDY; FEMALE ANIMAL; FREQUENCY MODULATION; GRYLLUS; GRYLLUS BIMACULATUS; GRYLLUS LOCOROJO; LINEAR SYSTEM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NONLINEAR SYSTEM; PRIORITY JOURNAL; SOUND INTENSITY; SOUND TRANSMISSION;

EID: 84880193554     PISSN: 09295313     EISSN: 15736873     Source Type: Journal    
DOI: 10.1007/s10827-013-0441-0     Document Type: Article

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