Computational Intelligence Based on Lattice Theory

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 t...

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Corporate Author: SpringerLink (Online service)
Other Authors: Kaburlasos, Vassilis G. (Editor), Ritter, Gerhard X. (Editor)
Format: eBook
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2007, 2007
Edition:1st ed. 2007
Series:Studies in Computational Intelligence
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of 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