Computational Intelligence Based on Lattice Theory

1. Front Matter

   Pages i-xvi

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2. Neural Computation

   1. Front Matter

      Pages 2-2

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   2. Granular Enhancement of Fuzzy ART/SOM Neural Classifiers Based on Lattice Theory

      • Vassilis G. Kaburlasos

      Pages 3-23

   3. Learning in Lattice Neural Networks that Employ Dendritic Computing

      • Gerhard X. Ritter, Gonzalo Urcid

      Pages 25-44

   4. Orthonormal Basis Lattice Neural Networks

      • Angelos Barmpoutis, Gerhard X. Ritter

      Pages 45-58

   5. Generalized Lattices Express Parallel Distributed Concept Learning

      • Michael J. Healy, Thomas P. Caudell

      Pages 59-77

3. Mathematical Morphology Applications

   1. Front Matter

      Pages 80-80

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   2. Noise Masking for Pattern Recall Using a Single Lattice Matrix Associative Memory

      • Gonzalo Urcid, Gerhard X. Ritter

      Pages 81-100

   3. Convex Coordinates From Lattice Independent Sets for Visual Pattern Recognition

      • Manuel Graña, Ivan Villaverde, Ramon Moreno, Francisco X. Albizuri

      Pages 101-128

   4. A Lattice-Based Approach to Mathematical Morphology for Greyscale and Colour Images

      • Valérie De Witte, Stefan Schulte, Mike Nachtegael, Tom Mélange, Etienne E. Kerre

      Pages 129-148

   5. Morphological and Certain Fuzzy Morphological Associative Memories for Classification and Prediction

      • Peter Sussner, Marcos Eduardo Valle

      Pages 149-171

4. Machine Learning Applications

   1. Front Matter

      Pages 174-174

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   2. The Fuzzy Lattice Reasoning (FLR) Classifier for Mining Environmental Data

      • Ioannis N. Athanasiadis

      Pages 175-193

   3. Machine Learning Techniques for Environmental Data Estimation

      • Vassilios Petridis, Vassilis Syrris

      Pages 195-214

   4. Application of Fuzzy Lattice Neurocomputing (FLN) in Ocean Satellite Images for Pattern Recognition

      • J. A. Piedra-Fernández, M. Cantón-Garbín, F. Guindos-Rojas

      Pages 215-232

   5. Genetically Engineered ART Architectures

      • Ahmad Al-Daraiseh, Assem Kaylani, Michael Georgiopoulos, Mansooreh Mollaghasemi, Annie S. Wu, Georgios Anagnostopoulos

      Pages 233-262

   6. Fuzzy Lattice Reasoning (FLR) Classification Using Similarity Measures

      • Al Cripps, Nghiep Nguyen

      Pages 263-284

5. Logic and Inference

   1. Front Matter

      Pages 286-286

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   2. Fuzzy Prolog: Default Values to Represent Missing Information

      • Susana Munoz-Hernandez, Claudio Vaucheret

      Pages 287-308

   3. Valuations on Lattices: Fuzzification and its Implications

      • Kevin H. Knuth

      Pages 309-324

A number of di?erent instruments for design can be uni?ed in the context of lattice theory towards cross-fertilization By“latticetheory”[1]wemean,equivalently,eitherapartialordering relation [2,3]ora couple of binary algebraic operations [3, 4]. There is a growing interest in computational intelligence based on lattice theory. A number of researchers are currently active developing lattice theory based models and techniques in engineering, computer and information s- ences, applied mathematics, and other scienti?c endeavours. Some of these models and techniques are presented here. However, currently, lattice theory is not part of the mainstream of com- tationalintelligence.Amajorreasonforthisisthe“learningcurve”associated with novel notions and tools. Moreover, practitioners of lattice theory, in s- ci?c domains of interest, frequently develop their own tools and/or practices without being aware of valuable contributions made by colleagues. Hence, (potentially) useful work may be ignored, or duplicated. Yet, other times, di?erent authors may introduce a con?icting terminology. The compilation of this book is an initiative towards proliferating est- lished knowledge in the hope to further expand it, soundly. There was a critical mass of people and ideas engaged to produce this book. Around two thirds of this book’s chapters are substantial enhancements of preliminary works presented lately in a three-part special session entitled “Computational Intelligence Based on Lattice Theory” organized in the c- text of the World Congress in Computational Intelligence (WCCI), FUZZ- IEEE program, July 16-21, 2006 in Vancouver, BC, Canada. The remaining book chapters are novel contributions by other researchers.

• Computational Intelligence
• Fuzzy
• Lattice Theory
• Prolog
• architecture
• cognition
• construction
• fuzzy set
• fuzzy sets
• intelligence
• learning
• machine learning
• neural network
• pattern analysis
• pattern recognition

• Technological Educational Institution of Kavala, Kavala, Greece

  Vassilis G. Kaburlasos

• University of Florida, Gainesville, USA

  Gerhard X. Ritter

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