Download or read book Pattern Recognition by Self organizing Neural Networks written by Gail A. Carpenter and published by MIT Press. This book was released on 1991 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields ofcognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19articles take up developments in competitive learning and computational maps, adaptive resonancetheory, and specialized architectures and biological connections. Introductorysurvey articles provide a framework for understanding the many models involved in various approachesto studying neural networks. These are followed in Part 2 by articles that form the foundation formodels of competitive learning and computational mapping, and recent articles by Kohonen, applyingthem to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designingadaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks,selforganizing pattern recognition systems whose top-down template feedback signals guarantee theirstable learning in response to arbitrary sequences of input patterns. In Part 4, articles describeembedding ART modules into larger architectures and provide experimental evidence fromneurophysiology, event-related potentials, and psychology that support the prediction that ARTmechanisms exist in the brain. Contributors: J.-P. Banquet, G.A. Carpenter, S.Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C.von der Malsburg, C.L. Winter.
Download or read book Competition and Cooperation in Neural Nets written by S. Amari and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: The human brain, wi th its hundred billion or more neurons, is both one of the most complex systems known to man and one of the most important. The last decade has seen an explosion of experimental research on the brain, but little theory of neural networks beyond the study of electrical properties of membranes and small neural circuits. Nonetheless, a number of workers in Japan, the United States and elsewhere have begun to contribute to a theory which provides techniques of mathematical analysis and computer simulation to explore properties of neural systems containing immense numbers of neurons. Recently, it has been gradually recognized that rather independent studies of the dynamics of pattern recognition, pattern format::ion, motor control, self-organization, etc. , in neural systems do in fact make use of common methods. We find that a "competition and cooperation" type of interaction plays a fundamental role in parallel information processing in the brain. The present volume brings together 23 papers presented at a U. S. -Japan Joint Seminar on "Competition and Cooperation in Neural Nets" which was designed to catalyze better integration of theory and experiment in these areas. It was held in Kyoto, Japan, February 15-19, 1982, under the joint sponsorship of the U. S. National Science Foundation and the Japan Society for the Promotion of Science. Participants included brain theorists, neurophysiologists, mathematicians, computer scientists, and physicists. There are seven papers from the U. S.
Download or read book Self Organizing Maps written by Teuvo Kohonen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book we have at hand is the fourth monograph I wrote for Springer Verlag. The previous one named "Self-Organization and Associative Mem ory" (Springer Series in Information Sciences, Volume 8) came out in 1984. Since then the self-organizing neural-network algorithms called SOM and LVQ have become very popular, as can be seen from the many works re viewed in Chap. 9. The new results obtained in the past ten years or so have warranted a new monograph. Over these years I have also answered lots of questions; they have influenced the contents of the present book. I hope it would be of some interest and help to the readers if I now first very briefly describe the various phases that led to my present SOM research, and the reasons underlying each new step. I became interested in neural networks around 1960, but could not in terrupt my graduate studies in physics. After I was appointed Professor of Electronics in 1965, it still took some years to organize teaching at the uni versity. In 1968 - 69 I was on leave at the University of Washington, and D. Gabor had just published his convolution-correlation model of autoasso ciative memory. I noticed immediately that there was something not quite right about it: the capacity was very poor and the inherent noise and crosstalk were intolerable. In 1970 I therefore sugge~ted the auto associative correlation matrix memory model, at the same time as J.A. Anderson and K. Nakano.
Download or read book Pattern Recognition Using Neural Networks written by Carl G. Looney and published by Oxford University Press on Demand. This book was released on 1997 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognizers evolve across the sections into perceptrons, a layer of perceptrons, multiple-layered perceptrons, functional link nets, and radial basis function networks. Other networks covered in the process are learning vector quantization networks, self-organizing maps, and recursive neural networks. Backpropagation is derived in complete detail for one and two hidden layers for both unipolar and bipolar sigmoid activation functions.
Download or read book Neural Networks for Applied Sciences and Engineering written by Sandhya Samarasinghe and published by CRC Press. This book was released on 2016-04-19 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in
Download or read book From Statistics to Neural Networks written by Vladimir Cherkassky and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NATO Advanced Study Institute From Statistics to Neural Networks, Theory and Pattern Recognition Applications took place in Les Arcs, Bourg Saint Maurice, France, from June 21 through July 2, 1993. The meeting brought to gether over 100 participants (including 19 invited lecturers) from 20 countries. The invited lecturers whose contributions appear in this volume are: L. Almeida (INESC, Portugal), G. Carpenter (Boston, USA), V. Cherkassky (Minnesota, USA), F. Fogelman Soulie (LRI, France), W. Freeman (Berkeley, USA), J. Friedman (Stanford, USA), F. Girosi (MIT, USA and IRST, Italy), S. Grossberg (Boston, USA), T. Hastie (AT&T, USA), J. Kittler (Surrey, UK), R. Lippmann (MIT Lincoln Lab, USA), J. Moody (OGI, USA), G. Palm (U1m, Germany), B. Ripley (Oxford, UK), R. Tibshirani (Toronto, Canada), H. Wechsler (GMU, USA), C. Wellekens (Eurecom, France) and H. White (San Diego, USA). The ASI consisted of lectures overviewing major aspects of statistical and neural network learning, their links to biological learning and non-linear dynamics (chaos), and real-life examples of pattern recognition applications. As a result of lively interactions between the participants, the following topics emerged as major themes of the meeting: (1) Unified framework for the study of Predictive Learning in Statistics and Artificial Neural Networks (ANNs); (2) Differences and similarities between statistical and ANN methods for non parametric estimation from examples (learning); (3) Fundamental connections between artificial learning systems and biological learning systems.
Download or read book Pattern Recognition Using Neural and Functional Networks written by Vasantha Kalyani David and published by Springer Science & Business Media. This book was released on 2008-11-20 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biologically inspiredcomputing isdi?erentfromconventionalcomputing.Ithas adi?erentfeel; often the terminology does notsound like it’stalkingabout machines.The activities ofthiscomputingsoundmorehumanthanmechanistic as peoplespeak ofmachines that behave, react, self-organize,learn, generalize, remember andeven to forget.Much ofthistechnology tries to mimic nature’s approach in orderto mimicsome of nature’s capabilities.They havearigorous, mathematical basisand neuralnetworks forexamplehaveastatistically valid set on which the network istrained. Twooutlinesaresuggestedasthepossibletracksforpatternrecognition.They are neuralnetworks andfunctionalnetworks.NeuralNetworks (many interc- nected elements operating in parallel) carryout tasks that are not only beyond the scope ofconventionalprocessing but also cannotbeunderstood in the same terms.Imagingapplicationsfor neuralnetworksseemtobea natural?t.Neural networks loveto do pattern recognition. A new approachto pattern recognition usingmicroARTMAP together with wavelet transforms in the context ofhand written characters,gestures andsignatures havebeen dealt.The KohonenN- work,Back Propagation Networks andCompetitive Hop?eld NeuralNetwork havebeen considered for various applications. Functionalnetworks,beingageneralizedformofNeuralNetworkswherefu- tionsarelearnedratherthanweightsiscomparedwithMultipleRegressionAn- ysisforsome applicationsandtheresults are seen to be coincident. New kinds of intelligence can be added to machines, and we will havethe possibilityof learningmore about learning.Thus our imaginationsand options are beingstretched.These new machines will be fault-tolerant,intelligentand self-programmingthustryingtomakethemachinessmarter.Soastomakethose who use the techniques even smarter. Chapter1 isabrief introduction toNeural and Functionalnetworks in the context of Patternrecognitionusing these disciplinesChapter2 givesa review ofthearchitectures relevantto the investigation andthedevelopment ofthese technologies in the past few decades. Retracted VIII Preface Chapter3begins with the lookattherecognition ofhandwritten alphabets usingthealgorithm for ordered list ofboundary pixelsas well as the Ko- nenSelf-Organizing Map (SOM).Chapter 4 describes the architecture ofthe MicroARTMAP and its capability.
Download or read book Artificial Neural Networks in Pattern Recognition written by Friedhelm Schwenker and published by Springer. This book was released on 2010-04-16 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Neural Networks in Pattern Recognition synthesizes the proceedings of the 4th IAPR TC3 Workshop, ANNPR 2010. Topics include supervised and unsupervised learning, feature selection, pattern recognition in signal and image processing.
Download or read book Self Organizing Neural Networks written by Udo Seiffert and published by Springer Science & Business Media. This book was released on 2001-09-25 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s, SOMs have been developed as a very powerful method for visualization and unsupervised classification tasks by an active and innovative community of interna tional researchers. A number of extensions and modifications have been developed during the last two decades. The reason is surely not that the original algorithm was imperfect or inad equate. It is rather the universal applicability and easy handling of the SOM. Com pared to many other network paradigms, only a few parameters need to be arranged and thus also for a beginner the network leads to useful and reliable results. Never theless there is scope for improvements and sophisticated new developments as this book impressively demonstrates. The number of published applications utilizing the SOM appears to be unending. As the title of this book indicates, the reader will benefit from some of the latest the oretical developments and will become acquainted with a number of challenging real-world applications. Our aim in producing this book has been to provide an up to-date treatment of the field of self-organizing neural networks, which will be ac cessible to researchers, practitioners and graduated students from diverse disciplines in academics and industry. We are very grateful to the father of the SOMs, Professor Teuvo Kohonen for sup porting this book and contributing the first chapter.
Download or read book Progress in Pattern Recognition Image Analysis and Applications written by Alberto Sanfeliu and published by Springer Science & Business Media. This book was released on 2004-10-15 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: First of all, we want to congratulate two new research communities from M- ico and Brazil that have recently joined the Iberoamerican community and the International Association for Pattern Recognition. We believe that the series of congresses that started as the “Taller Iberoamericano de Reconocimiento de Patrones (TIARP)”, and later became the “Iberoamerican Congress on Pattern Recognition (CIARP)”, has contributed to these groupconsolidatione?orts. We hope that in the near future all the Iberoamerican countries will have their own groups and associations to promote our areas of interest; and that these congresses will serve as the forum for scienti?c research exchange, sharing of - pertise and new knowledge, and establishing contacts that improve cooperation between research groups in pattern recognition and related areas. CIARP 2004 (9th Iberoamerican Congress on Pattern Recognition) was the ninthinaseriesofpioneeringcongressesonpatternrecognitionintheIberoam- ican community. As in the previous year, CIARP 2004 also included worldwide participation. It took place in Puebla, Mexico. The aim of the congress was to promote and disseminate ongoing research and mathematical methods for pattern recognition, image analysis, and applications in such diverse areas as computer vision, robotics, industry, health, entertainment, space exploration, telecommunications, data mining, document analysis,and natural languagep- cessing and recognition, to name a few.
Download or read book Neural Networks for Pattern Recognition written by Christopher M. Bishop and published by Oxford University Press. This book was released on 1995-11-23 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.
Download or read book Self organization and Associative Memory written by Teuvo Kohonen and published by Springer. This book was released on 1984 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Information Security and Assurance written by Samir Kumar Bandyopadhyay and published by Springer Science & Business Media. This book was released on 2010-06-09 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Science and Technology, Advanced Communication and Networking, Information Security and Assurance, Ubiquitous Computing and Multimedia Appli- tions are conferences that attract many academic and industry professionals. The goal of these co-located conferences is to bring together researchers from academia and industry as well as practitioners to share ideas, problems and solutions relating to the multifaceted aspects of advanced science and technology, advanced communication and networking, information security and assurance, ubiquitous computing and m- timedia applications. This co-located event included the following conferences: AST 2010 (The second International Conference on Advanced Science and Technology), ACN 2010 (The second International Conference on Advanced Communication and Networking), ISA 2010 (The 4th International Conference on Information Security and Assurance) and UCMA 2010 (The 2010 International Conference on Ubiquitous Computing and Multimedia Applications). We would like to express our gratitude to all of the authors of submitted papers and to all attendees, for their contributions and participation. We believe in the need for continuing this undertaking in the future. We acknowledge the great effort of all the Chairs and the members of advisory boards and Program Committees of the above-listed events, who selected 15% of over 1,000 submissions, following a rigorous peer-review process. Special thanks go to SERSC (Science & Engineering Research Support soCiety) for supporting these - located conferences.
Download or read book Pattern Recognition and Neural Networks written by Brian D. Ripley and published by Cambridge University Press. This book was released on 2007 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.
Download or read book Adaptive Pattern Recognition and Neural Networks written by Yoh-Han Pao and published by Addison Wesley Publishing Company. This book was released on 1989 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: A coherent introduction to the basic concepts of pattern recognition, incorporating recent advances from AI, neurobiology, engineering, and other disciplines. Treats specifically the implementation of adaptive pattern recognition to neural networks. Annotation copyright Book News, Inc. Portland, Or.
Download or read book Principles of Data Mining and Knowledge Discovery written by Jan Zytkow and published by Springer Science & Business Media. This book was released on 1999-09-01 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'99, held in Prague, Czech Republic in September 1999. The 28 revised full papers and 48 poster presentations were carefully reviewed and selected from 106 full papers submitted. The papers are organized in topical sections on time series, applications, taxonomies and partitions, logic methods, distributed and multirelational databases, text mining and feature selection, rules and induction, and interesting and unusual issues.
Download or read book Artificial Neural Networks in Pattern Recognition written by Nadia Mana and published by Springer. This book was released on 2012-09-11 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th INNS IAPR TC3 GIRPR International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2012, held in Trento, Italy, in September 2012. The 21 revised full papers presented were carefully reviewed and selected for inclusion in this volume. They cover a large range of topics in the field of neural network- and machine learning-based pattern recognition presenting and discussing the latest research, results, and ideas in these areas.
