| Description |
1 online resource (xvi, 375 pages) : illustrations (some color) |
| Series |
Studies in Computational Intelligence, 1860-949X ; 67 |
|
Studies in computational intelligence ; 67. 1860-949X
|
| Contents |
Neural Computation -- Granular Enhancement of Fuzzy ART/SOM Neural Classifiers Based on Lattice Theory -- Learning in Lattice Neural Networks that Employ Dendritic Computing -- Orthonormal Basis Lattice Neural Networks -- Generalized Lattices Express Parallel Distributed Concept Learning -- Mathematical Morphology Applications -- Noise Masking for Pattern Recall Using a Single Lattice Matrix Associative Memory -- Convex Coordinates From Lattice Independent Sets for Visual Pattern Recognition -- A Lattice-Based Approach to Mathematical Morphology for Greyscale and Colour Images -- Morphological and Certain Fuzzy Morphological Associative Memories for Classification and Prediction -- Machine Learning Applications -- The Fuzzy Lattice Reasoning (FLR) Classifier for Mining Environmental Data -- Machine Learning Techniques for Environmental Data Estimation -- Application of Fuzzy Lattice Neurocomputing (FLN) in Ocean Satellite Images for Pattern Recognition -- Genetically Engineered ART Architectures -- Fuzzy Lattice Reasoning (FLR) Classification Using Similarity Measures -- Logic and Inference -- Fuzzy Prolog: Default Values to Represent Missing Information -- Valuations on Lattices: Fuzzification and its Implications -- L-fuzzy Sets and Intuitionistic Fuzzy Sets -- A Family of Multi-valued t-norms and t-conorms -- The Construction of Fuzzy-valued t-norms and t-conorms |
| Summary |
The emergence of lattice theory within the field of computational intelligence (CI) is partially due to its proven effectiveness in neural computation. Moreover, lattice theory has the potential to unify a number of diverse concepts and aid in the cross-fertilization of both tools and ideas within the numerous subfields of CI. The compilation of this eighteen-chapter book is an initiative towards proliferating established knowledge in the hope to further expand it. This edited book is a balanced synthesis of four parts emphasizing, in turn, neural computation, mathematical morphology, machine learning, and (fuzzy) inference/logic. The articles here demonstrate how lattice theory may suggest viable alternatives in practical clustering, classification, pattern analysis, and regression applications |
| Bibliography |
Includes bibliographical references and index |
| Notes |
English |
|
Print version record |
| In |
OhioLINK electronic book center |
|
SpringerLink |
| Subject |
Computational intelligence.
|
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Lattice theory.
|
|
Lattice theory.
|
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Computational intelligence.
|
|
Ingénierie.
|
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Computational intelligence
|
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Lattice theory
|
| Form |
Electronic book
|
| Author |
Kaburlasos, Vassilis G
|
|
Ritter, G. X
|
| LC no. |
2007927312 |
| ISBN |
9783540726876 |
|
354072687X |
|
9783540726869 |
|
3540726861 |
|
128094420X |
|
9781280944208 |
|
9786610944200 |
|
6610944202 |
|
