In practical cluster analysis tasks, an efficient clustering algorithm should be less sensitive to
parameter configurations and tolerate the existence of outliers. Based on the neural gas …

Cortical activity evoked by repeated identical sensory stimulation is extremely variable. The
source of this variability is often assigned to “random ongoing background activity” which is …

This paper attempts to incorporate the structure of the cerebellar-model-articulation-
controller (CMAC) network into the Kohonen layer of the self-organizing map (SOM) to …

A “roulette-wheel” routine (Genetic Algorithms in Search, Optimization and Machine
Learning, Addison-Wesley, Reading, MA, 1989) for random sampling is adopted as a means …

Design of polymer-based, chemo-responsive chemical sensors for a given set of target
vapors is a challenging task, as the detailed mechanism of the sensing phenomena is still …

In this paper, we present a novel robust neural gas (RNG) algorithm. While retaining the
essence of the original neural gas (NG) algorithm, the RNG algorithm effectively tackles the …

This paper gives a brief description of a hierarchical architecture (HONG) that has been
described in Atukorale and Suganthan (Neurocomputing 35 (2000) 165). The learning …

This paper examines the neural gas networks proposed by Martinetz and Schulten and
Fritzke in an effort to create a more biologically plausible hybrid version. The hybrid …

This paper presents a new growing neural network for cluster analysis and market
segmentation, which optimizes the size and structure of clusters by iteratively checking them …

Neural gas is basically an artificial neural network, motivated through a self-organising map.
The neural gas approach has been successfully applied to clustering, image processing and …