Supervised and unsupervised pattern recognition : feature extraction and computational intelligence

著者

• Micheli-Tzanakou, Evangelia

書誌事項

Supervised and unsupervised pattern recognition : feature extraction and computational intelligence

Evangelia Micheli-Tzanakou

（Industrial electronics series）

CRC Press, c2000

注記

Includes bibliographical references and index

内容説明・目次

内容説明

There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images. This substantial collection of recent research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy neural networks and their applications to handwritten character recognition and recognition of normal and abnormal visual evoked potentials. The third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional NN architecture simulating brain functions. The final section discusses general applications and simulations, such as the establishment of a brain-computer link, speaker identification, and face recognition. In the quickly changing field of computational intelligence, every discovery is significant. Supervised and Unsupervised Pattern Recognition gives you access to many notable findings in one convenient volume.

目次

classifiers-an overview Criteria for optimal classifier design Categorizing the Classifiers Classifiers Neural Networks Comparison of Experimental Results System Performance Assessment Analysis of Prediction Rates from Bootstrapping Assessment ARTIFICIAL NEURAL NETWORKS: DEFINITIONS, METHODS, APPLICATIONS Definitions Training Algorithm Some Applications A SYSTEM FOR HANDWRITTEN DIGIT RECOGNITION Preprocessing of Handwritten Digit Images Zernike Moments (ZM) for Characterization of Image Patterns Dimensionality Reduction Analysis of Prediction Error Rates from Bootstrapping Assessment Summary OTHER TYPES OF FEATURE EXTRACTION METHODS Introduction Wavelets Invariant Moments Entropy Cepstrum Analysis Fractal Dimension Entropy SGLD Texture Features FUZZY NEURAL NETWORKS Pattern Recognition Optimization System Design Clustering APPLICATION TO HANDWRITTEN DIGITS Introduction to Character Recognition Data Collection Results Discussion Summary A UNSUPERVISED NEURAL NETWORK SYSTEM FOR VISUAL EVOKED POTENTIALS Data Collection and Preprocessing System Design Results Discussion CLASSIFICATION OF MAMMOGRAMS USING A MODULAR NEURAL NETWORK Methods and System Overview Modular Neural Networks Neural Network Training Classification Results The Process of Obtaining Results ALOPEX Parameters Generalization Conclusions "VISUAL OPHTHALMOLOGIST": AN AUTOMATED SYSTEM FOR CLASSIFICATION OF RETINAL DAMAGE System Overview Modular Neural Networks Applications to Ophthalmology Results Discussion A THREE-DIMENSIONAL NEURAL NETWORK ARCHITECTURE The Neural Network Architecture Simulations Discussion A FEATURE EXTRACTION ALGORITHM USING CONNECTIVITY STRENGTHS AND MOMENT INVARIANTS ALOPEX Algorithms Moment Invariants and ALOPEX Results and Discussion MULTILAYER PERCEPTRONS WITH ALOPEX: 2D-TEMPLATE MATCHING AND VLSI IMPLEMENTATION Multilayer Perceptron and Template Matching VLSI Implementation of ALOPEX IMPLEMENTING NEURAL NETWORKS IN SILICON The Living Neuron Neuromorphic Models Neurological Process Modeling SPEAKER IDENTIFICATION THROUGH WAVELET MULTIRESOLUTION DECOMPOSITION AND ALOPEX Multiresolution Analysis through Wavelet Decomposition Pattern Recognition with ALOPEX Methods Results Discussion FACE RECOGNITION IN ALZHEIMER'S DISEASE: A SIMULATION Methods Results Discussion SELF-LEARNING LAYERED NEURAL NETWORKS Neocognition and Pattern Classification Objectives Methods Study A Study B Summary and Discussion BIOLOGICAL AND MACHINE VISION Distributed Representation The Model A Modified ALOPEX Algorithm Application to Template Matching Brain-to-Computer Link Discussion Each section also has an introduction and references

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詳細情報

• NII書誌ID(NCID): BA47025268
• ISBN:
  • 0849322782
• LCCN: 99043495
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: Boca Raton, Fla.
• ページ数/冊数: 371p.
• 大きさ: 25 cm
• 分類:
  • LCC : TK7882.P3
  • DC21 : 006.4
• 件名:
  • LCSH : Pattern recognition systems
  • LCSH : Neural networks (Computer science)
• 親書誌ID:
  • BA47024913