The classification of biological data.
Abstract |
We develop a Data Mining system to assist with the elucidation by graphical means of the biochemical changes in the brains of rodents. Manual analysis of such experiments is increasingly impractical because of the voluminous ... |
|
Abstract |
This article analyses the match tracking anomaly (MTA) of the ARTMAP neural network. The anomaly arises when an input pattern exactly matches its category prototype that the network has previously learned, and the network ... |
|
Abstract |
Analysis of patterns of temporal variation in community dynamics was conducted by combining two unsupervised artificial neural networks, the Adaptive Resonance Theory (ART) and the Kohonen network. The field data used as ... |
|
Abstract |
A new type of classifier combining an unsupervised and a supervised model was designed and applied to classification of malignant and benign masses on mammograms. The unsupervised model was based on an adaptive resonance ... |
|
Abstract |
A machine vision system is described to sort the regenerated plants of gladiolus into groups using trichromatic features of leaves. The machine vision system consisted of a scanner, image analysis software and an adaptive ... |
|
Abstract |
Dividing the acoustic repertoires of animals into biologically relevant categories presents a widespread problem in the study of animal sound communication, essential to any comparison of repertoires between contexts, ... |
|
Abstract |
Artificial neural networks have shown to be a powerful tool for system modelling in a wide range of applications. In this paper, we focus on neural network applications to intelligent data analysis in the field of animal ... |
|
Abstract |
We report on the development of an electronic tongue as potential tool for fish freshness determination. The studies were carried out following the evolution with time on fillet of cultured sea bream (Sparus Auratus). The ... |
|
Abstract |
Photometric clustering of regenerated plants of gladiolus was described using fuzzy adaptive resonance theory (ART) and the resultant grouping pattern was compared with ART 2, and self-organizing map (SOM) neural network ... |
|
Abstract |
Adaptive resonance theory (ART) describes a class of artificial neural network architectures that act as classification tools which self-organize, work in realtime, and require no retraining to classify novel sequences. We ... |
|
Abstract |
The concentration of a substance, such as glucose, in a biological sample, such as human tissue (e.g. the skin of an index finger) is non-invasively determined by directing the output beam of a laser diode onto and into the ... |
|
Abstract |
This paper describes new properties of competitive systems which arise in population biology, ecology, psychophysiology, and developmental biology. These properties yield a global method for analyzing the geometric design ... |
|
Abstract |
This paper shows how knowledge, in the form of fuzzy rules, can be derived from a supervised learning neural network called furry ARTMAP. Rule extraction proceeds in two stages: pruning, which simplifies the network ... |
|
Abstract |
Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi?sensor, data fusion. Single-channel Fusion ARTMAP is functionally equivalent to Fuzzy ART during unsupervised learning and to Fuzzy ... |
|
Description |
The code allows for the creation, training, and testing of a Fuzzy ARTMAP neural network system. The following example datasets are also included in the zip file.
- Stripes benchmark (sparse)
- Stripes benchmark
... |
|
Description |
This entry contains the software, implemented in the KDE Integrated NeuroSimulation Software (KInNeSS ) that simulates the Synchronous Matching Adaptive Resonance Theory. SMART was first described in Grossberg and Versace ... |
|