Neural Geographies
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Neural Geographies
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Author : Elizabeth A. Wilson
language : en
Publisher: Routledge
Release Date : 2016-02-04
Neural Geographies written by Elizabeth A. Wilson and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-04 with Philosophy categories.
Neural Geographies draws together recent feminist and deconstructive theories, early Freudian neurology and contemporary connectionist theories of cognition. In this original work, Elizabeth A. Wilson explores the convergence between Derrida, Freud and recent cognitive theory to pursue two important issues: the nature of cognition and neurology, and the politics of feminist and critical interventions into contemporary scientific psychology. This book seeks to reorient the usual presumptions of critical studies of the sciences by addressing the divisions between the static and the changeable; the natural and the political; the neuro-cognitive and the cultural that have been traditional to both scientific and critical accounts of neurology and cognition.
Neural Geographies
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Author : Elizabeth Ann Wilson
language : en
Publisher: Psychology Press
Release Date : 1998
Neural Geographies written by Elizabeth Ann Wilson and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Social Science categories.
This volume traces the modern critical and performance history of this play, one of Shakespeare's most-loved and most-performed comedies. The essay focus on such modern concerns as feminism, deconstruction, textual theory, and queer theory.
Neural Nets Applications In Geography
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Author : B. Hewitson
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Neural Nets Applications In Geography written by B. Hewitson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
Neural nets offer a fascinating new strategy for spatial analysis, and their application holds enormous potential for the geographic sciences. However, the number of studies that have utilized these techniques is limited. This lack of interest can be attributed, in part, to lack of exposure, to the use of extensive and often confusing jargon, and to the misapprehension that, without an underlying statistical model, the explanatory power of the neural net is very low. Neural Nets: Applications for Geography attacks all three issues; the text demonstrates a wide variety of neural net applications in geography in a simple manner, with minimal jargon. The volume presents an introduction to neural nets that describes some of the basic concepts, as well as providing a more mathematical treatise for those wishing further details on neural net architecture. The bulk of the text, however, is devoted to descriptions of neural net applications in such broad-ranging fields as census analysis, predicting the spread of AIDS, describing synoptic controls on mountain snowfall, examining the relationships between atmospheric circulation and tropical rainfall, and the remote sensing of polar cloud and sea ice characteristics. The text illustrates neural nets employed in modes analogous to multiple regression analysis, cluster analysis, and maximum likelihood classification. Not only are the neural nets shown to be equal or superior to these more conventional methods, particularly where the relationships have a strong nonlinear component, but they are also shown to contain significant explanatory power. Several chapters demonstrate that the nets themselves can be decomposed to illuminate causative linkages between different events in both the physical and human environments.
Spatial Cognition
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Author : R. Lloyd
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Spatial Cognition written by R. Lloyd and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Science categories.
10.2 Summary of Ideas ..................................................... 256 10.2.1 Spatial Behavior As Rules For Decision Making ................................... 258 10.2.2. Cognitive Mapping ......................................................................... 258 10.2.3. Storing Information ................................................. " ...................... 260 10.2.4. Searching ..................................................................................... 260 10.2.5. Learning ........................................................................................ 261 10.2.6. Judging Similarity .......................................................................... 261 10.2.7 Neural Geographic Information Science (NGIS) .................................... 262 REFERENCES ............................................... 265 INDEX ........................ .............. 279 ACKNOWLEDGEMENTS ................................... 287 x LIST OF TABLES Table 8.1: The types of similarity comparisons created for the experiment to determine the effect ofx as a first or second common or distinctive feature (Lloyd, Rostkowska-Covington, and Steinke 1996). Table 9.1: Data used to compute the gravity model using regression and a neural network. Data for all variables are scaled so that the highest value equals 0.9 and the lowest value equals 0.1. Table 9.2: Class means for 11 socio-economic and life-cycle variables for the Black, Integrated, and White classes. Table 9.3: Weights for neuron at row 5 and column 1 that learned the blue horizontal rectangle map symbol. LIST OF FIGURES Figure 1.1: Spatial cognition is a research area of interest for both geography and psychology. Both disciplines are interested in fundamental ideas related to encoding processes, internal representations, and decoding processes. Figure 1.2: The place names on this map of New Orleans depict the propositions used for navigation by local residents. A similar map appeared in the June 30, 1991, edition of The Times-Picayune.
Neurocomputation In Remote Sensing Data Analysis
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Author : Ioannis Kanellopoulos
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Neurocomputation In Remote Sensing Data Analysis written by Ioannis Kanellopoulos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
A state-of-the-art view of recent developments in the use of artificial neural networks for analysing remotely sensed satellite data. Neural networks, as a new form of computational paradigm, appear well suited to many of the tasks involved in this image analysis. This book demonstrates a wide range of uses of neural networks for remote sensing applications and reports the views of a large number of European experts brought together as part of a concerted action supported by the European Commission.
Geophysical Applications Of Artificial Neural Networks And Fuzzy Logic
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Author : W. Sandham
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Geophysical Applications Of Artificial Neural Networks And Fuzzy Logic written by W. Sandham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Mathematics categories.
The past fifteen years has witnessed an explosive growth in the fundamental research and applications of artificial neural networks (ANNs) and fuzzy logic (FL). The main impetus behind this growth has been the ability of such methods to offer solutions not amenable to conventional techniques, particularly in application domains involving pattern recognition, prediction and control. Although the origins of ANNs and FL may be traced back to the 1940s and 1960s, respectively, the most rapid progress has only been achieved in the last fifteen years. This has been due to significant theoretical advances in our understanding of ANNs and FL, complemented by major technological developments in high-speed computing. In geophysics, ANNs and FL have enjoyed significant success and are now employed routinely in the following areas (amongst others): 1. Exploration Seismology. (a) Seismic data processing (trace editing; first break picking; deconvolution and multiple suppression; wavelet estimation; velocity analysis; noise identification/reduction; statics analysis; dataset matching/prediction, attenuation), (b) AVO analysis, (c) Chimneys, (d) Compression I dimensionality reduction, (e) Shear-wave analysis, (f) Interpretation (event tracking; lithology prediction and well-log analysis; prospect appraisal; hydrocarbon prediction; inversion; reservoir characterisation; quality assessment; tomography). 2. Earthquake Seismology and Subterranean Nuclear Explosions. 3. Mineral Exploration. 4. Electromagnetic I Potential Field Exploration. (a) Electromagnetic methods, (b) Potential field methods, (c) Ground penetrating radar, (d) Remote sensing, (e) inversion.
Artificial Neural Networks In Hydrology
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Author : R.S. Govindaraju
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Artificial Neural Networks In Hydrology written by R.S. Govindaraju and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Science categories.
R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.
Neural Networks And Animal Behavior
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Author : Magnus Enquist
language : en
Publisher: Princeton University Press
Release Date : 2013-12-03
Neural Networks And Animal Behavior written by Magnus Enquist and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-03 with Science categories.
How can we make better sense of animal behavior by using what we know about the brain? This is the first book that attempts to answer this important question by applying neural network theory. Scientists create Artificial Neural Networks (ANNs) to make models of the brain. These networks mimic the architecture of a nervous system by connecting elementary neuron-like units into networks in which they stimulate or inhibit each other's activity in much the same way neurons do. This book shows how scientists can employ ANNs to analyze animal behavior, explore the general principles of the nervous systems, and test potential generalizations among species. The authors focus on simple neural networks to show how ANNs can be investigated by math and by computers. They demonstrate intuitive concepts that make the operation of neural networks more accessible to nonspecialists. The first chapter introduces various approaches to animal behavior and provides an informal introduction to neural networks, their history, and their potential advantages. The second chapter reviews artificial neural networks, including biological foundations, techniques, and applications. The following three chapters apply neural networks to such topics as learning and development, classical instrumental condition, and the role of genes in building brain networks. The book concludes by comparing neural networks to other approaches. It will appeal to students of animal behavior in many disciplines. It will also interest neurobiologists, cognitive scientists, and those from other fields who wish to learn more about animal behavior.
Brain Culture
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Author : Davi Johnson Thornton
language : en
Publisher: Rutgers University Press
Release Date : 2011
Brain Culture written by Davi Johnson Thornton and has been published by Rutgers University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Business & Economics categories.
Brain Culture investigates the American obsession with the health of the brain. Davi Johnson Thornton looks at familiar messages, tracing how brain science and colorful brain images produced by scientific technologies are taken up and distributed in popular media. She tracks the message that, "you are your brain" across multiple contemporary contexts, analyzing its influence on child development, family life, education, and public policy. Our fixation on the brain is not simply a reaction to scientific progress, but a cultural phenomenon tied to values of individualism and limitless achievement.
The Application Of Neural Networks In The Earth System Sciences
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Author : Vladimir M. Krasnopolsky
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-14
The Application Of Neural Networks In The Earth System Sciences written by Vladimir M. Krasnopolsky and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-14 with Science categories.
This book brings together a representative set of Earth System Science (ESS) applications of the neural network (NN) technique. It examines a progression of atmospheric and oceanic problems, which, from the mathematical point of view, can be formulated as complex, multidimensional, and nonlinear mappings. It is shown that these problems can be solved utilizing a particular type of NN – the multilayer perceptron (MLP). This type of NN applications covers the majority of NN applications developed in ESSs such as meteorology, oceanography, atmospheric and oceanic satellite remote sensing, numerical weather prediction, and climate studies. The major properties of the mappings and MLP NNs are formulated and discussed. Also, the book presents basic background for each introduced application and provides an extensive set of references. “This is an excellent book to learn how to apply artificial neural network methods to earth system sciences. The author, Dr. Vladimir Krasnopolsky, is a universally recognized master in this field. With his vast knowledge and experience, he carefully guides the reader through a broad variety of problems found in the earth system sciences where neural network methods can be applied fruitfully. (...) The broad range of topics covered in this book ensures that researchers/graduate students from many fields (...) will find it an invaluable guide to neural network methods.” (Prof. William W. Hsieh, University of British Columbia, Vancouver, Canada) “Vladimir Krasnopolsky has been the “founding father” of applying computation intelligence methods to environmental science; (...) Dr. Krasnopolsky has created a masterful exposition of a young, yet maturing field that promises to advance a deeper understanding of best modeling practices in environmental science.” (Dr. Sue Ellen Haupt, National Center for Atmospheric Research, Boulder, USA) “Vladimir Krasnopolsky has written an important and wonderful book on applications of neural networks to replace complex and expensive computational algorithms within Earth System Science models. He is uniquely qualified to write this book, since he has been a true pioneer with regard to many of these applications. (...) Many other examples of creative emulations will inspire not just readers interested in the Earth Sciences, but any other modeling practitioner (...) to address both theoretical and practical complex problems that may (or will!) arise in a complex system." ” (Prof. Eugenia Kalnay, University of Maryland, USA)