Literature DB >> 18491168

An autocorrelation model of bat sonar.

Lutz Wiegrebe1.   

Abstract

Their sonar system allows echolocating bats to navigate with high skill through a complex, three- dimensional environment at high speed and low light. The auditory analysis of the echoes of their ultrasonic sounds requires a detailed comparison of the emission and echoes. Here an auditory model of bat sonar is introduced and evaluated against a set of psychophysical phantom-target, echo-acoustic experiments. The model consists of a relatively detailed simulation of auditory peripheral processing in the bat, Phyllostomus discolor, followed by a functional module consisting of a strobed, normalised, autocorrelation in each frequency channel. The model output is accumulated in a sonar image buffer. The model evaluation is based on the comparison of the image-buffer contents generated in individually simulated psychophysical trials. The model provides reasonably good predictions for both temporal and spectral behavioural sonar processing in terms of sonar delay-, roughness, and phase sensitivity and in terms of sensitivity to the temporal separations in two-front targets and the classification of spectrally divergent phantom targets.

Entities:  

Mesh:

Year:  2008        PMID: 18491168     DOI: 10.1007/s00422-008-0216-2

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  17 in total

Review 1.  Complex echo classification by echo-locating bats: a review.

Authors:  Yossi Yovel; Matthias O Franz; Peter Stilz; Hans-Ulrich Schnitzler
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2010-09-17       Impact factor: 1.836

2.  Bioinspired sonar reflectors as guiding beacons for autonomous navigation.

Authors:  Ralph Simon; Stefan Rupitsch; Markus Baumann; Huan Wu; Herbert Peremans; Jan Steckel
Journal:  Proc Natl Acad Sci U S A       Date:  2020-01-06       Impact factor: 11.205

Review 3.  Click-based echolocation in bats: not so primitive after all.

Authors:  Yossi Yovel; Maya Geva-Sagiv; Nachum Ulanovsky
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2011-04-05       Impact factor: 1.836

4.  A comprehensive computational model of animal biosonar signal processing.

Authors:  Chen Ming; Stephanie Haro; Andrea Megela Simmons; James A Simmons
Journal:  PLoS Comput Biol       Date:  2021-02-17       Impact factor: 4.475

5.  Size does not matter: size-invariant echo-acoustic object classification.

Authors:  Daria Genzel; Lutz Wiegrebe
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2012-11-24       Impact factor: 1.836

6.  Biosonar resolving power: echo-acoustic perception of surface structures in the submillimeter range.

Authors:  Ralph Simon; Mirjam Knörnschild; Marco Tschapka; Annkathrin Schneider; Nadine Passauer; Elisabeth K V Kalko; Otto von Helversen
Journal:  Front Physiol       Date:  2014-02-26       Impact factor: 4.566

7.  An exploratory study on 99mTc-RGD-BBN peptide scintimammography in the assessment of breast malignant lesions compared to 99mTc-3P4-RGD2.

Authors:  Qianqian Chen; Qingjie Ma; Minglong Chen; Bin Chen; Qiang Wen; Bing Jia; Fan Wang; Butong Sun; Shi Gao
Journal:  PLoS One       Date:  2015-04-07       Impact factor: 3.240

8.  Size constancy in bat biosonar? Perceptual interaction of object aperture and distance.

Authors:  Melina Heinrich; Lutz Wiegrebe
Journal:  PLoS One       Date:  2013-04-22       Impact factor: 3.240

9.  What a plant sounds like: the statistics of vegetation echoes as received by echolocating bats.

Authors:  Yossi Yovel; Peter Stilz; Matthias O Franz; Arjan Boonman; Hans-Ulrich Schnitzler
Journal:  PLoS Comput Biol       Date:  2009-07-03       Impact factor: 4.475

10.  Object localization using a biosonar beam: how opening your mouth improves localization.

Authors:  G Arditi; A J Weiss; Y Yovel
Journal:  R Soc Open Sci       Date:  2015-08-26       Impact factor: 2.963

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.