Pattern Recognition With Neural Networks In C

Author : Abhijit S. Pandya,Robert B. Macy
Publisher : CRC Press
Page : 434 pages
File Size : 41,9 Mb
Release : 2020-10-12
Category : Computers
ISBN : 9780429606212

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Pattern Recognition with Neural Networks in C++ by Abhijit S. Pandya,Robert B. Macy Pdf

The addition of artificial neural network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical guide to the application of artificial neural networks. Geared toward the practitioner, Pattern Recognition with Neural Networks in C++ covers pattern classification and neural network approaches within the same framework. Through the book's presentation of underlying theory and numerous practical examples, readers gain an understanding that will allow them to make judicious design choices rendering neural application predictable and effective. The book provides an intuitive explanation of each method for each network paradigm. This discussion is supported by a rigorous mathematical approach where necessary. C++ has emerged as a rich and descriptive means by which concepts, models, or algorithms can be precisely described. For many of the neural network models discussed, C++ programs are presented for the actual implementation. Pictorial diagrams and in-depth discussions explain each topic. Necessary derivative steps for the mathematical models are included so that readers can incorporate new ideas into their programs as the field advances with new developments. For each approach, the authors clearly state the known theoretical results, the known tendencies of the approach, and their recommendations for getting the best results from the method. The material covered in the book is accessible to working engineers with little or no explicit background in neural networks. However, the material is presented in sufficient depth so that those with prior knowledge will find this book beneficial. Pattern Recognition with Neural Networks in C++ is also suitable for courses in neural networks at an advanced undergraduate or graduate level. This book is valuable for academic as well as practical research.

Author : Abhijit S. Pandya,Robert B. Macy
Publisher : CRC Press
Page : 432 pages
File Size : 55,7 Mb
Release : 2019-12-17
Category : Electronic
ISBN : 0367448874

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Pattern Recognition with Neural Networks in C++ by Abhijit S. Pandya,Robert B. Macy Pdf

The addition of artificial network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is presented in this practical guide to the application of artificial neural networks. The material covered in the book is accessible to working engineers with little or no explicit background in neural networks.

Author : Christopher M. Bishop
Publisher : Oxford University Press
Page : 501 pages
File Size : 45,5 Mb
Release : 1995-11-23
Category : Computers
ISBN : 9780198538646

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Neural Networks for Pattern Recognition by Christopher M. Bishop Pdf

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.

Author : Chi Hau Chen
Publisher : World Scientific
Page : 176 pages
File Size : 46,8 Mb
Release : 1991-12-27
Category : Computers
ISBN : 9789814505994

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Neural Networks In Pattern Recognition And Their Applications by Chi Hau Chen Pdf

The revitalization of neural network research in the past few years has already had a great impact on research and development in pattern recognition and artificial intelligence. Although neural network functions are not limited to pattern recognition, there is no doubt that a renewed progress in pattern recognition and its applications now critically depends on neural networks. This volume specially brings together outstanding original research papers in the area and aims to help the continued progress in pattern recognition and its applications.

Author : Patrick S P Wang,Isabelle Guyon
Publisher : World Scientific
Page : 329 pages
File Size : 44,7 Mb
Release : 1994-01-01
Category : Electronic
ISBN : 9789814611817

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Advances In Pattern Recognition Systems Using Neural Network Technologies by Patrick S P Wang,Isabelle Guyon Pdf

Contents:A Connectionist Approach to Speech Recognition (Y Bengio)Signature Verification Using a “Siamese” Time Delay Neural Network (J Bromley et al.)Boosting Performance in Neural Networks (H Drucker et al.)An Integrated Architecture for Recognition of Totally Unconstrained Handwritten Numerals (A Gupta et al.)Time-Warping Network: A Neural Approach to Hidden Markov Model Based Speech Recognition (E Levin et al.)Computing Optical Flow with a Recurrent Neural Network (H Li & J Wang)Integrated Segmentation and Recognition through Exhaustive Scans or Learned Saccadic Jumps (G L Martin et al.)Experimental Comparison of the Effect of Order in Recurrent Neural Networks (C B Miller & C L Giles)Adaptive Classification by Neural Net Based Prototype Populations (K Peleg & U Ben-Hanan)A Neural System for the Recognition of Partially Occluded Objects in Cluttered Scenes: A Pilot Study (L Wiskott & C von der Malsburg)and other papers Readership: Computer scientists and engineers.

Author : Steven K. Rogers,Matthew Kabrisky
Publisher : SPIE Press
Page : 240 pages
File Size : 46,7 Mb
Release : 1991
Category : Computers
ISBN : 0819405345

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An Introduction to Biological and Artificial Neural Networks for Pattern Recognition by Steven K. Rogers,Matthew Kabrisky Pdf

Author : Vladimir Cherkassky,Jerome H. Friedman,Harry Wechsler
Publisher : Springer Science & Business Media
Page : 414 pages
File Size : 47,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642791192

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From Statistics to Neural Networks by Vladimir Cherkassky,Jerome H. Friedman,Harry Wechsler Pdf

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.

Author : Brian D. Ripley
Publisher : Cambridge University Press
Page : 420 pages
File Size : 47,5 Mb
Release : 2007
Category : Computers
ISBN : 0521717701

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Pattern Recognition and Neural Networks by Brian D. Ripley Pdf

This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.

Author : Ernst Kussul,Tatiana Baidyk,Donald C. Wunsch
Publisher : Springer Science & Business Media
Page : 225 pages
File Size : 48,5 Mb
Release : 2009-12-01
Category : Computers
ISBN : 9783642025358

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Neural Networks and Micromechanics by Ernst Kussul,Tatiana Baidyk,Donald C. Wunsch Pdf

Micromechanical manufacturing based on microequipment creates new possibi- ties in goods production. If microequipment sizes are comparable to the sizes of the microdevices to be produced, it is possible to decrease the cost of production drastically. The main components of the production cost - material, energy, space consumption, equipment, and maintenance - decrease with the scaling down of equipment sizes. To obtain really inexpensive production, labor costs must be reduced to almost zero. For this purpose, fully automated microfactories will be developed. To create fully automated microfactories, we propose using arti?cial neural networks having different structures. The simplest perceptron-like neural network can be used at the lowest levels of microfactory control systems. Adaptive Critic Design, based on neural network models of the microfactory objects, can be used for manufacturing process optimization, while associative-projective neural n- works and networks like ART could be used for the highest levels of control systems. We have examined the performance of different neural networks in traditional image recognition tasks and in problems that appear in micromechanical manufacturing. We and our colleagues also have developed an approach to mic- equipment creation in the form of sequential generations. Each subsequent gene- tion must be of a smaller size than the previous ones and must be made by previous generations. Prototypes of ?rst-generation microequipment have been developed and assessed.

Author : H Bunke,A Kandel
Publisher : World Scientific
Page : 276 pages
File Size : 54,7 Mb
Release : 2000-12-22
Category : Computers
ISBN : 9789814492393

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Neuro-Fuzzy Pattern Recognition by H Bunke,A Kandel Pdf

Neural networks and fuzzy techniques are among the most promising approaches to pattern recognition. Neuro-fuzzy systems aim at combining the advantages of the two paradigms. This book is a collection of papers describing state-of-the-art work in this emerging field. It covers topics such as feature selection, classification, classifier training, and clustering. Also included are applications of neuro-fuzzy systems in speech recognition, land mine detection, medical image analysis, and autonomous vehicle control. The intended audience includes graduate students in computer science and related fields, as well as researchers at academic institutions and in industry. Contents: Methodology:Simultaneous Feature Analysis and System Identification in a Neuro-Fuzzy Framework (N R Pal & D Chakraborty)Neuro-Fuzzy Model for Unsupervised Feature Extraction with Real Life Applications (R K De et al.)A Computational-Intelligence-Based Approach to Decision Support (M B Gorzalczany)Clustering Problem Using Fuzzy C-Means Algorithms and Unsupervised Neural Networks (J-S Lin)Automatic Training of Min-Max Classifiers (A Rizzi)Granular Computing in Pattern Recognition (W Pedrycz & G Vukovich)ART-Based Model Set for Pattern Recognition: FasArt Family (G I Sainz Palmero et al.)Applications:A Methodology and a System for Adaptive Speech Recognition in a Noisy Environment Based on Adaptive Noise Cancellation and Evolving Fuzzy Neural Networks (N Kasabov & G Iliev)Neural Versus Heuristic Development of Choquet Fuzzy Integral Fusion Algorithms for Land Mine Detection (P D Gader et al.)Automatic Segmentation of Multi-Spectral MR Brain Images Using a Neuro-Fuzzy Algorithm (S Y Lee et al.)Vision-Based Neuro-Fuzzy Control of Autonomous Lane Following Vehicle (Y-J Ryoo) Readership: Graduate students, lecturers and researchers in computer science and computer engineering. Keywords:Neuro-Fuzzy;Fuzzy Logic;Neural Networks;Pattern Recognition;Classification;Clustering;Decision Making;Uncertainty Management

Author : Menahem Friedman,Abraham Kandel
Publisher : World Scientific
Page : 350 pages
File Size : 49,5 Mb
Release : 1999
Category : Computers
ISBN : 9810233124

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Introduction to Pattern Recognition by Menahem Friedman,Abraham Kandel Pdf

This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.

Author : Albert Nigrin
Publisher : MIT Press
Page : 450 pages
File Size : 53,9 Mb
Release : 1993
Category : Computers
ISBN : 0262140543

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Neural Networks for Pattern Recognition by Albert Nigrin Pdf

In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural networks by Stephen Grossberg and his colleagues to a new level. In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Following a tutorial of existing neural networks for pattern classification, Nigrin expands on these networks to present fundamentally new architectures that perform realtime pattern classification of embedded and synonymous patterns and that will aid in tasks such as vision, speech recognition, sensor fusion, and constraint satisfaction. Nigrin presents the new architectures in two stages. First he presents a network called Sonnet 1 that already achieves important properties such as the ability to learn and segment continuously varied input patterns in real time, to process patterns in a context sensitive fashion, and to learn new patterns without degrading existing categories. He then removes simplifications inherent in Sonnet 1 and introduces radically new architectures. These architectures have the power to classify patterns that may have similar meanings but that have different external appearances (synonyms). They also have been designed to represent patterns in a distributed fashion, both in short-term and long-term memory.

Author : Vasantha Kalyani David,S. Rajasekaran
Publisher : Springer Science & Business Media
Page : 198 pages
File Size : 43,9 Mb
Release : 2008-11-20
Category : Mathematics
ISBN : 9783540851295

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Pattern Recognition Using Neural and Functional Networks by Vasantha Kalyani David,S. Rajasekaran Pdf

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.

Author : Friedhelm Schwenker,Neamat El Gayar
Publisher : Springer Science & Business Media
Page : 283 pages
File Size : 45,6 Mb
Release : 2010-03-25
Category : Computers
ISBN : 9783642121586

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Artificial Neural Networks in Pattern Recognition by Friedhelm Schwenker,Neamat El Gayar Pdf

This book constitutes the refereed proceedings of the 4th IAPR TC3 Workshop, ANNPR 2010, held in Cairo, Eqypt, in April 2010. The 23 revised full papers presented were carefully reviewed and selected from 42 submissions. The major topics of ANNPR are supervised and unsupervised learning, feature selection, pattern recognition in signal and image processing, and applications in data mining or bioinformatics.

Author : Sameer Singh,Maneesha Singh,Chid Apte,Petra Perner
Publisher : Springer
Page : 814 pages
File Size : 51,5 Mb
Release : 2005-10-03
Category : Computers
ISBN : 9783540319993

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Pattern Recognition and Image Analysis by Sameer Singh,Maneesha Singh,Chid Apte,Petra Perner Pdf

This LNCS volume contains the papers presented at the 3rd International Conference on Advances in Pattern Recognition (ICAPR 2005) organized in August, 2005 in the beautiful city of Bath, UK.