Dendritic computing has been proved to produce perfect approximation of any data
distribution. This result guarantees perfect accuracy training. However, we have found great …

Background. Lattice theory extends into virtually every branch of mathematics, ranging from
measure theory and convex geometry to probability theory and topology. A more recent …

Dementia is a growing concern due to the aging process of the western societies. Non-
invasive detection is therefore a high priority research endeavor. In this paper we report …

Most fuzzy associative memories (FAMs) in the literature correspond to neural networks with
a single layer of weights that distributively contains the information on associations to be …

We focus on two aspects of the face recognition, feature extraction and classification. We
propose a two component system, introducing Lattice Independent Component Analysis …

By “fusion” this work means integration of disparate types of data including (intervals of) real
numbers as well as possibility/probability distributions defined over the totally-ordered lattice …

Many well-known fuzzy associative memory (FAM) models can be viewed as (fuzzy)
morphological neural networks (MNNs) because they perform an operation of (fuzzy) …

This work proposes an effective synergy of the Intervals׳ Number k-nearest neighbor (INknn)
classifier, that is a granular extension of the conventional knn classifier in the metric lattice of …

Defining a relation between granules and computing ever-changing granules are two
important issues in granular computing. In view of this, this work proposes a partial order …

This work introduces a Type-II fuzzy lattice reasoning (FLRtypeII) scheme for
learning/generalizing novel 2D shape representations. A 2D shape is represented as an …