Generalizing Operations of Binary Autoassociative Morphological Memories Using Fuzzy Set Theory
Journal of Mathematical Imaging and Vision
Fuzzy lattice reasoning (FLR) classifier and its application for ambient ozone estimation
International Journal of Approximate Reasoning
A general framework for fuzzy morphological associative memories
Fuzzy Sets and Systems
Lattice Independence and Vision Based Mobile Robot Navigation
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
An introduction to morphological perceptrons with competitive learning
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Permutation-based finite implicative fuzzy associative memories
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
A class of hybrid morphological perceptrons with application in time series forecasting
Knowledge-Based Systems
An evolutionary approach to design dilation-erosion perceptrons for stock market indices forecasting
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Morphological neural networks and vision based mobile robot navigation
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Lattice neural networks with spike trains
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
A novel lattice associative memory based on dendritic computing
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Fuzzy lattice reasoning for pattern classification using a new positive valuation function
Advances in Fuzzy Systems
Learning parsimonious dendritic classifiers
Neurocomputing
Active Learning with Bootstrapped Dendritic Classifier applied to medical image segmentation
Pattern Recognition Letters
Multi-argument fuzzy measures on lattices of fuzzy sets
Knowledge-Based Systems
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Recent advances in the biophysics of computation and neurocomputing models have brought to the foreground the importance of dendritic structures in a single neuron cell. Dendritic structures are now viewed as the primary autonomous computational units capable of realizing logical operations. By changing the classic simplified model of a single neuron with a more realistic one that incorporates the dendritic processes, a novel paradigm in artificial neural networks is being established. In this work, we introduce and develop a mathematical model of dendrite computation in a morphological neuron based on lattice algebra. The computational capabilities of this enriched neuron model are demonstrated by means of several illustrative examples and by proving that any single layer morphological perceptron endowed with dendrites and their corresponding input and output synaptic processes is able to approximate any compact region in higher dimensional Euclidean space to within any desired degree of accuracy. Based on this result, we describe a training algorithm for single layer morphological perceptrons and apply it to some well-known nonlinear problems in order to exhibit its performance.