Adaptive Resonance theory was introduced by Grossberg to address the stability versus plasticity dilemma. That is, how can one design a learning system that is plastic enough to learn new information, and at the same time stable enough not to forget old, important information that it has already learned. In the past two decades a number of ART neural network architectures were introduced in the...

The fuzzy ARTMAP neural network is used to classify data that is incomplete in one or more ways. These include a limited number of training cases, missing components, missing class labels, and missing classes. Modifications for dealing with such incomplete data are introduced, and performance is assessed on an emitter identification task using a data base of radar pulses.

Quality control of essential oils is an important topic in industrial processing of medicinal and aromatic plants. In this paper, the performance of Fuzzy Adaptive Resonant Theory Map (ARTMAP) and linear discriminant analysis (LDA) algorithms are compared in the specific task of quality classification of Rosa damascene essential oil samples (one of the most famous and valuable essential oils in...

0020-0255/$ see front matter 2010 Elsevier Inc doi:10.1016/j.ins.2010.02.026 * Corresponding author. E-mail addresses: [email protected] (J.-F In many practical applications, new information may emerge from the environment at different points in time after a classification system has originally been deployed. For instance, in biometric systems, new data may be acquired and used to enro...

Part I of this paper proposes a definition of the adaptive resonance theory (ART) class of constructive unsupervised on-line learning clustering networks. Class ART generalizes several well-known clustering models, e.g., ART 1, improved ART 1, adaptive Hamming net (AHN), and Fuzzy ART, which are optimized in terms of memory storage and/or computation time. Next, the symmetric Fuzzy ART (S-Fuzzy...

The article addresses comparison of fuzzy BKproduct approach with A* search algorithm for optimal path finding of the autonomous underwater vehicles (AUVs). The technique is designed to accomplish two missions: obstacle avoidance using ARTMAP and fuzzy BK-product and comparison of optimal path finding with A* search algorithm. In the first mission, underwater obstacle avoidance technique has al...

Incidents on the freeway disrupt traffic flow and the cost of delay caused by the incidents is significant. To reduce the impact of an incident a traffic management center needs to quickly detect and remove it from the freeway. In this vein quick and efficient automatic incident detection has been the main goal of the transportation research for many years. Also many algorithms based on loop de...

The performance of speech-processing systems such as speech coding, speech recognition has been degraded by background environmental noises such as car, bus, babble, factory, helicopter and street noise. Noise classification is essential to enhance the performance. A major step in the design of a signal classification system is the selection of a good set of features that are capable of separat...