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Clustering with neural networks
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Analog VLSI Implementation of Neural Systems
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Self-Organization and Associative Memory
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An introduction to probability theory and its applications
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Algorithms for clustering data
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Cluster Analysis for Applications
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Algorithms for Clustering Data
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Numerical Initial Value Problems in Ordinary Differential Equations
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Learning Internal Representations by Error Propagation
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An Introduction to Probability Theory and Its Applications
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Numerical Initial Value Problems in Ordinary Differential Equations
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An Introduction to Probability Theory and Its Applications.
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An Algorithm for Euclidean Sum of Squares Classification
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Parallel Distributed Processing
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Network Optimization Methods in Passivity-Based Cooperative Control
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Clustering and Neural Networks
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Non-linear Approach to Grouping, Dynamics and Organizational Informatics of Benthic Macroinvertebrate Communities in Streams by Artificial Neural Networks
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Hopfield Model and Optimization Problems
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Retail segmentation using artificial neural networks
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Evaluating the Appropriateness of Market Segmentation Solutions Using Artificial Neural Networks and the Membership Clustering Criterion
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A stochastic connectionist approach for global optimization with application to pattern clustering
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Optimization neural networks for the segmentation of magnetic resonance images
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Continuous optimization schemes for fuzzy classification
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Penalized K-Means Algorithms for Finding the Number of Clusters
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Cluster analysis using self-organizing maps and image processing techniques
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On problem solving with Hopfield neural networks
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Solving inversion problems with neural networks
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Deep Belief Networks Oriented Clustering
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Predictive neural clustering system and its applications to bacteria properties predictions
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Clustering with mean field annealing and unsupervised learning
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Clustering of complex shaped data sets via Kohonen maps and mathematical morphology
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Estimating the Number of Clusters in Multivariate Data by Self-Organizing Maps
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A comparison of unsupervised neural networks and k-means clustering in the analysis of multi-element stream sediment data
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Neural Networks for Combinatorial Optimization: A Review of More Than a Decade of Research
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Egg Size Variation in Blue TitsCyanistes caeruleusand Great TitsParus majorin Relation to Habitat Differences in Snail Abundance
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Clustering Based on Continuous Hopfield Network
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Determination of the Number of Clusters in a Data Set
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Applications of Neural Networks in Supply Chain Management
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Determination of the Number of Clusters in a Data Set
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Penalized k-means algorithms for finding the correct number of clusters in a dataset
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