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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Journal ArticleDOI
An optical water type framework for selecting and blending retrievals from bio-optical algorithms in lakes and coastal waters.
TL;DR: This work presents an approach to manage the shift from blue/green ratios to red/NIR-based chlorophyll-a algorithms for optically complex waters, and examines the use of this approach in several coastal marine environments and the long-term frequency of the OWTs to MODIS-Aqua imagery over Lake Erie.
Journal ArticleDOI
Integrating a fuzzy k-means classification and a Bayesian approach for spatial prediction of landslide hazard
TL;DR: A robust method for spatial prediction of landslide hazard in roaded and roadless areas of forest is described, based on assigning digital terrain attributes into continuous landform classes through a fuzzy k-means approach.
Dissertation
Latent variable models for neural data analysis
TL;DR: This dissertation attempts to meet this need, extending and applying the modern tools of latent variable modeling to problems in neural data analysis, by proposing a new, extremely general, optimization algorithm that may be used to learn the optimal parameter values of arbitrary latent variable models.
Journal ArticleDOI
Automatic detection and quantification of stiction in control valves
TL;DR: In this article, a model free method that can detect and quantify stiction that may be present in control valves using routine operating data obtained from the process is described, which can be used to diagnose and diagnose stiction.
Journal ArticleDOI
Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System
Yizhang Jiang,Dongrui Wu,Zhaohong Deng,Pengjiang Qian,Jun Wang,Guanjin Wang,Fu-Lai Chung,Kup-Sze Choi,Shitong Wang +8 more
TL;DR: Transductive transfer learning is used to reduce the discrepancy in data distribution between the training and testing data, semi-supervised learning is employed to use the unlabeled testing data to remedy the shortage of training data, and TSK fuzzy system is adopted to increase model interpretability.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters
TL;DR: In this paper, two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space, and the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the LSE criterion function.