000 04983nam a22003498i 4500
001 CR9780511779145
003 UkCbUP
005 20200124160317.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 100519s2010||||enk o ||1 0|eng|d
020 _a9780511779145 (ebook)
020 _z9780521763950 (hardback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aQP441
_b.M63 2010
082 0 0 _a612.8/2
_222
245 0 0 _aModelling perception with artificial neural networks /
_c[edited by] Colin R. Tosh, Graeme D. Ruxton.
264 1 _aCambridge :
_bCambridge University Press,
_c2010.
300 _a1 online resource (x, 397 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505 0 0 _gPart I. General themes:
_g1.
_tNeural networks for perceptual processing: from simulation tools to theories /
_rKevin Gurney;
_g2.
_tSensory ecology and perceptual allocation: new prospects for neural networks /
_rSteven M. Phelps --
_gPart II.
_tThe use of artificial neural networks to elucidate the nature of perceptual processes in animals:
_g3.
_tCorrelation versus gradient type motion detectors: the pros and cons /
_rAlexander Borst;
_g4.
_tSpatial constancy and the brain: insights from neural networks /
_rRobert L. White III and Lawrence H. Snyder;
_g5.
_tThe interplay of Pavlovian and instrumental processes in devaluation experiments: a computational embodied neuroscience model tested with a simulated rat /
_rFrancesco Mannella, Marco Mirolli and Gianluca Baldassarre;
_g6.
_tEvolution, (sequential) learning and generalization in modular and nonmodular visual neural networks /
_rRaffae.e Calabretta;
_g7.
_tEffects of network structure on associative memory /
_rHiraku Oshima and Tokashi Odagaki;
_g8.
_tNeural networks and neuro-oncology: the complex interplay between brain tumour, epilepsy and cognition /
_rL. Douw [and others] --
_gPart III.
_tArtificial neural networks as models of perceptual processing in ecology and evolutionary biology:
_g9.
_tEvolutionary diversification of mating behaviour: using artificial neural networks to study reproductive character displacement and speciation /
_rKarin S. Pfennig and Michael J. Ryan;
_g10.
_tApplying artificial neural networks to the study of prey coloration /
_rSami Merilaita;
_g11.
_tArtificial neural networks in models of specialization, guild evolution and sympatric speciation /
_rNoél M.A. Holmgren, Niclas. Norrstrom and Wayne M. Getz;
_g12.
_tProbabilistic design principles for robust multimodal communication networks /
_rDavid C. Krakauer, Jessica Flack and Nihat Ay;
_g13.
_tMovement-based signalling and the physical world: modelling the changing perceptual task for receivers /
_rRichard A. Peters --
_gPart IV.
_tMethodological issues in the use of simple feedforward networks:
_g14.
_tHow training and testing histories affect generalization: a test of simple neural networks /
_rStefano Ghirlanda and Magnus Enquist;
_g15.
_tThe need for stochastic replication of ecological neural networks /
_rColin R. Tosh and Graeme D. Ruxton;
_g16.
_tMethodological issues in modelling ecological learning with neural networks /
_rDaniel W. Franks and Graeme D. Ruxton;
_g17.
_tNeural network evolution and artificial life research /
_rDara Curran and Colin O'Riordan;
_g18.
_tCurrent velocity shapes the functional connectivity of benthiscapes to stream insect movement /
_rJulian D. Olden;
_g19.
_tA model biological neural network: the cephalopod vestibular system /
_rRoddy Williamson and Abdul Chrachri.
520 _aStudies of the evolution of animal signals and sensory behaviour have more recently shifted from considering 'extrinsic' (environmental) determinants to 'intrinsic' (physiological) ones. The drive behind this change has been the increasing availability of neural network models. With contributions from experts in the field, this book provides a complete survey of artificial neural networks. The book opens with two broad, introductory level reviews on the themes of the book: neural networks as tools to explore the nature of perceptual mechanisms, and neural networks as models of perception in ecology and evolutionary biology. Later chapters expand on these themes and address important methodological issues when applying artificial neural networks to study perception. The final chapter provides perspective by introducing a neural processing system in a real animal. The book provides the foundations for implementing artificial neural networks, for those new to the field, along with identifying potential research areas for specialists.
650 0 _aPerception
_xComputer simulation.
650 0 _aNeural networks (Computer science)
700 1 _aTosh, Colin,
_eeditor.
700 1 _aRuxton, Graeme D.,
_eeditor.
776 0 8 _iPrint version:
_z9780521763950
856 4 0 _uhttps://doi.org/10.1017/CBO9780511779145
999 _c521547
_d521545