Pattern Recognition Using Neural And Functional Networks
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Pattern Recognition Using Neural And Functional Networks
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Author : Vasantha Kalyani David
language : en
Publisher: Springer
Release Date : 2010-11-16
Pattern Recognition Using Neural And Functional Networks written by Vasantha Kalyani David and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-16 with Mathematics categories.
The concept of pattern is universal in intelligence. This book recounts recent progress in pattern recognition using neural networks and functional networks, including wavelet transforms in the context of handwritten characters, gestures and signatures.
Pattern Recognition Using Neural And Functional Networks
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Author : Vasantha Kalyani David
language : en
Publisher:
Release Date : 2010
Pattern Recognition Using Neural And Functional Networks written by Vasantha Kalyani David and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Neural networks (Computer science) categories.
The concept of pattern is universal in intelligence. This book recounts recent progress in pattern recognition using neural networks and functional networks, including wavelet transforms in the context of handwritten characters, gestures and signatures.
Pattern Recognition Using Neural And Functional Networks
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Author : Vasantha Kalyani David
language : en
Publisher: Springer
Release Date : 2014-05-14
Pattern Recognition Using Neural And Functional Networks written by Vasantha Kalyani David and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-14 with Mathematics categories.
The concept of pattern is universal in intelligence. This book recounts recent progress in pattern recognition using neural networks and functional networks, including wavelet transforms in the context of handwritten characters, gestures and signatures.
Neural Networks In Pattern Recognition And Their Applications
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Author : Chi-hau Chen
language : en
Publisher: World Scientific
Release Date : 1991
Neural Networks In Pattern Recognition And Their Applications written by Chi-hau Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Computers categories.
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.
Neural Networks For Pattern Recognition
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Author : Christopher M. Bishop
language : en
Publisher: Oxford University Press
Release Date : 1995-11-23
Neural Networks For Pattern Recognition written by Christopher M. Bishop and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-11-23 with Computers categories.
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.
Pattern Recognition With Neural Networks In C
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Author : Abhijit S. Pandya
language : en
Publisher: CRC Press
Release Date : 1995-10-17
Pattern Recognition With Neural Networks In C written by Abhijit S. Pandya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-10-17 with Computers categories.
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.
Artificial Neural Networks In Pattern Recognition
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Author : Nadia Mana
language : en
Publisher: Springer
Release Date : 2012-09-11
Artificial Neural Networks In Pattern Recognition written by Nadia Mana and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-11 with Computers categories.
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.
Advances In Pattern Recognition Systems Using Neural Network Technologies
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Author : Patrick S P Wang
language : en
Publisher: World Scientific
Release Date : 1994-01-01
Advances In Pattern Recognition Systems Using Neural Network Technologies written by Patrick S P Wang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-01-01 with categories.
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.
Pattern Recognition Using Neural Networks
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Author : Carl G. Looney
language : en
Publisher: Oxford University Press on Demand
Release Date : 1997
Pattern Recognition Using Neural Networks written by Carl G. Looney and has been published by Oxford University Press on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
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.
Artificial Neural Networks And Statistical Pattern Recognition
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Author : I.K. Sethi
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Artificial Neural Networks And Statistical Pattern Recognition written by I.K. Sethi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.
With the growing complexity of pattern recognition related problems being solved using Artificial Neural Networks, many ANN researchers are grappling with design issues such as the size of the network, the number of training patterns, and performance assessment and bounds. These researchers are continually rediscovering that many learning procedures lack the scaling property; the procedures simply fail, or yield unsatisfactory results when applied to problems of bigger size. Phenomena like these are very familiar to researchers in statistical pattern recognition (SPR), where the curse of dimensionality is a well-known dilemma. Issues related to the training and test sample sizes, feature space dimensionality, and the discriminatory power of different classifier types have all been extensively studied in the SPR literature. It appears however that many ANN researchers looking at pattern recognition problems are not aware of the ties between their field and SPR, and are therefore unable to successfully exploit work that has already been done in SPR. Similarly, many pattern recognition and computer vision researchers do not realize the potential of the ANN approach to solve problems such as feature extraction, segmentation, and object recognition. The present volume is designed as a contribution to the greater interaction between the ANN and SPR research communities.