04948cam a22003374a 4500 16128460 OSt 20150408114136.0 100310s2010 nyua b 001 0 eng 2010010418 9780521763950 (OCoLC)ocn569508969 Ma-Un pcc QP441 .M63 2010 612.82 22 MOP Modelling perception with artificial neural networks / [edited by] Colin R. Tosh, Graeme D. Ruxton. New York : Cambridge University Press, 2010. x, 397 p. : ill. ; 26 cm. Includes bibliographical references and index. Part I. General themes: 1. Neural networks for perceptual processing: from simulation tools to theories / Kevin Gurney; 2. Sensory ecology and perceptual allocation: new prospects for neural networks / Steven M. Phelps -- Part II. The use of artificial neural networks to elucidate the nature of perceptual processes in animals: 3. Correlation versus gradient type motion detectors: the pros and cons / Alexander Borst; 4. Spatial constancy and the brain: insights from neural networks / Robert L. White III and Lawrence H. Snyder; 5. The interplay of Pavlovian and instrumental processes in devaluation experiments: a computational embodied neuroscience model tested with a simulated rat / Francesco Mannella, Marco Mirolli and Gianluca Baldassarre; 6. Evolution, (sequential) learning and generalization in modular and nonmodular visual neural networks / Raffae.e Calabretta; 7. Effects of network structure on associative memory / Hiraku Oshima and Tokashi Odagaki; 8. Neural networks and neuro-oncology: the complex interplay between brain tumour, epilepsy and cognition / L. Douw ... [et al.] -- Part III. Artificial neural networks as models of perceptual processing in ecology and evolutionary biology: 9. Evolutionary diversification of mating behaviour: using artificial neural networks to study reproductive character displacement and speciation / Karin S. Pfennig and Michael J. Ryan; 10. Applying artificial neural networks to the study of prey coloration / Sami Merilaita; 11. Artificial neural networks in models of specialization, guild evolution and sympatric speciation / No�el M. A. Holmgren, Niclas. Norrstrom and Wayne M. Getz; 12. Probabilistic design principles for robust multimodal communication networks / David C. Krakauer, Jessica Flack and Nihat Ay; 13. Movement-based signalling and the physical world: modelling the changing perceptual task for receivers / Richard A. Peters -- Part IV. Methodological issues in the use of simple feedforward networks: 14. How training and testing histories affect generalization: a test of simple neural networks / Stefano Ghirlanda and Magnus Enquist; 15. The need for stochastic replication of ecological neural networks / Colin R. Tosh and Graeme D. Ruxton; 16. Methodological issues in modelling ecological learning with neural networks / Daniel W. Franks and Graeme D. Ruxton; 17. Neural network evolution and artificial life research / Dara Curran and Colin O'Riordan; 18. Current velocity shapes the functional connectivity of benthiscapes to stream insect movement / Julian D. Olden; 19. A model biological neural network: the cephalopod vestibular system / Roddy Williamson and Abdul Chrachri. "Studies 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"-- Perception Computer simulation. 16312 Neural networks (Computer science) Tosh, Colin. 36421 Ruxton, Graeme D. 36422 Cover image http://assets.cambridge.org/97805217/63950/cover/9780521763950.jpg 7 cbc orignew 1 ecip 20 y-gencatlg ddc BOOK 30307 264807 0 2013-08-04 0 1 612.82 MOP 1 2013-08-04 CL 00205804 CL 2013-08-04 00:00:00 BOOK ddc 0 0 2013-10-22 0 0 612.82 MOP 2 2013-10-22 CL 00207095 CL 2013-10-22 00:00:00 BOOK ddc 0 0 2013-10-22 0 0 612.82 MOP 3 2013-10-22 CL 00207094 CL 2013-10-22 00:00:00 BOOK ddc 0