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Articles & Tech Transfers


GUI4GUI user guide
Abstract Frequently, a computer program requires input parameters to define a specific application prior to running it. For codes that require few input parameters, the usual method to define these parameters is to store them in a ...

Soft-clustering and improved stability for adaptive resonance theory neural networks
Abstract Stability and plasticity in learning systems are both equally essential, but achieving stability and plasticity simultaneously is difficult. Adaptive resonance theory (ART) neural networks are known for their plastic and ...

Adaptive categorization of ART networks in robot behavior learning using game theoretic formulation
Abstract Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to ...

A modified ART 1 algorithm more suitable for VLSI implementations
Abstract This paper presents a modification to the original ART 1 algorithm (Carpenter & Grossberg, 1987a, A massively parallel architecture for a self-organizing neural pattern recognition machine, Computer Vision, Graphics, and ...

Online pattern classification with multiple neural network systems: An experimental study
Abstract In this paper, an empirical study of the development and application of a committee of neural networks on online pattern classification tasks is presented. A multiple classifier framework is designed by adopting an Adaptive ...

Study of distributed learning as a solution to category proliferation in Fuzzy ARTMAP based neural systems
Abstract An evaluation of distributed learning as a means to attenuate the category proliferation problem in Fuzzy ARTMAP based neural systems is carried out. from both qualitative and quantitative points of view. The study involves ...

Modified ART 2A growing network capable of generating a fixed number of nodes
Abstract This paper introduces the Adaptive Resonance Theory under Constraint (ART-C 2A) learning paradigm based on ART 2A, which is capable of generating a user-defined number of recognition nodes through online estimation of an ...

Colour image segmentation using the self-organizing map and adaptive resonance theory
Abstract We propose a new competitive-learning neural network model for colour image segmentation. The model, which is based on the adaptive resonance theory (ART) of Carpenter and Grossberg and on the self-organizing map (SOM) of ...

An intelligent video categorization engine
Abstract Purpose - We describe an intelligent video categorization engine (IVCE) that uses the learning capability of artificial neural networks (ANNs) to classify suitably preprocessed video segments into a predefined number of ...

Application of a noisy data classification technique to determine the occurrence of flashover in compartment fires
Abstract This paper presents a hybrid Artificial Neural Network (ANN) model that is developed for noisy data classification. The model, named GRNNFA, is a fusion of the Fuzzy Adaptive Resonance Theory (FA) model and the General ...

A low-power current mode fuzzy-ART cell
Abstract This paper presents a very large scale integration (VLSI) implementation of a low-power current-mode fuzzy-adaptive resonance theory (ART) cell. The cell is based on a compact new current source multibit memory cell with ...

Part family formation through fuzzy ART2 neural network
Abstract In order to overcome some unavoidable factors, like shift of the part, that influence the crisp neural networks recognition, the present study is dedicated in developing a novel fuzzy neural network (FNN), which integrates ...

Extensions of vector quantization for incremental clustering
Abstract In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental online learning. This is motivated in the ...

Integrating temporal difference methods and self-organizing neural networks for reinforcement learning with delayed evaluative feedback
Abstract This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal ...

Hybrid optoelectronic adaptive resonance theory neural processor, ART1
Abstract For industrial use, adaptive resonance theory (ART) neural networks have the potential of becoming an important component in a variety of commercial and military systems. Efficient software emulations of these networks are ...

Supervised adaptive resonance theory neural network for modelling dynamic systems
Abstract A supervised neural network, SMART2, has been developed which can be used with the ART2 algorithm for modelling discrete dynamic systems. A new layer has been added as a higher transformation stage to provide an output ...

Application specific intelligent microsensors
Abstract An intelligent microsensor module (10, 100, 210, 300, 355, 410) is provided that can fuse data streams from a variety of sources and then locally determine the current state of the environment in which the intelligent ...

Use of generic classifiers to determine physical topology in heterogeneous networking environments
Abstract Round trip time, bottleneck link speed, and hop count information from one node to the remaining nodes within a network is collected and processed by an adaptive resonance theory (ART) neural network to classify the nodes by ...

Category regions as new geometrical concepts in Fuzzy-ART and Fuzzy-ARTMAP
Abstract In this paper we introduce novel geometric concepts, namely category regions, in the original framework of Fuzzy-ART (FA) and Fuzzy- ARTMAP (FAM). The definitions of these regions are based on geometric interpretations of ...

Adaptive resonance associative map
Abstract This article introduces a neural architecture termed Adaptive Resonance Associative Map (ARAM) that extends unsupervised Adaptive Resonance Theory (ART) systems for rapid, yet stable, heteroassociative learning. ARAM can be ...

Some physiological and biochemical consequences of psychological postulates
Abstract This note lists some psychological, physiological, and biochemical predictions that have been derived from simple psychological postu]ates. These psychological postulates have been used to derive a nev learning theory, 1-3 ...

Neural expectation: Cerebellar and retinal analogs of cells fired by learnable or unlearned pattern classes
Abstract Neural networks are introduced which can be taught by classical or instrumental conditioning to fire in response to arbitrary learned classes of patterns. The filters of output cells are biased by presetting cells whose ...

Spiking threshold and overarousal effects in serial learning
Abstract Possible dependencies of serial learning data on physiological parameters such as spiking thresholds, arousal level, and decay rate of potentials are considered in a rigorous learning model. Influence of these parameters on ...

On the dynamics of operant conditioning
Abstract Simple psychological postulates are presented which are used to derivepossible anatomical and physiological substrates of operant conditioning.These substrates are compatible with much psychological data aboutoperants. A ...

Pavlovian pattern learning by nonlinear neural networks
Abstract This note describes laws for the anatomy, potentials, spiking rules, and transmitters of some networks of formal neurons that enable them to learn spatial patterns by Pavlovian conditioning. Applications to spacetime pattern ...

Embedding fields: Underlying philosophy, mathematics, and applications to psychology, physiology, and anatomy
Abstract This article reviews results on a learning theory that can be derived from simple psychological postulates and given a suggestive neurophysiological, anatomical, and biochemical interpretation. The neural networks described ...

A what-and-where fusion neural network for recognition and tracking of multiple radar emitters
Abstract A neural network recognition and tracking system is proposed for classification of radar pulses in autonomous Electronic Support Measure systems. Radar type information is considered with position-specific information from ...

A model of movement coordinates in the motor cortex: Posture-dependent changes in the gain and direction of single cell tuning curves
Abstract This article outlines a methodology for investigating the coordinate systems by which movement variables are encoded in the firing rates of individual motor cortical neurons. Recent neurophysiological experiments have probed ...

WSOM: Building adaptive wavelets with self-organizing maps
Abstract The WSOM (wavelet self-organizing map) model, a neural network for the creation of wavelet bases adapted to the distribution of input data, is introduced. The model provides an efficient online method to construct ...

Information fusion for image analysis: Geospatial foundations for higher-level fusion
Abstract In support of the AFOSR program in Information Fusion, the CNS Technology Laboratory at Boston University is developing and applying neural models of image and signal processing, pattern learning and recognition, associative ...

Classification of Incomplete Data Using the Fuzzy ARTMAP Neural Network
Abstract 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 ...