| Abstract |
A Fuzzy ARTMAP classifier for pattern recognition in chemical sensor array was developed based on Fuzzy Set Theory and Adaptive Resonance Theory. In contrast to most current classifiers with difficulty in detecting new ... |
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This paper focuses on classification problems, and in particular on the evolution of ARTMAP architectures using genetic algorithms, with the objective of improving generalization performance and alleviating the adaptive ... |
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This paper presents a Fuzzy ARTMAP (FAM) based modular architecture for multi-class pattern recognition known as Modular Adaptive Resonance Theory Map (MARTMAP). The prediction of class membership is made collectively by ... |
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Auditory signals of speech are speaker dependent, but representations of language meaning are speaker independent. The transformation from speaker-dependent to speaker-independent language representations enables speech to ... |
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This paper presents a comparative analysis of novel supervised fuzzy adaptive resonance theory (SF-ART), multilayer perceptron (MLP) and Multi Layer Perceptrons (MLP) neural networks over Ballistocardiogram (BCG) signal ... |
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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 ... |
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This paper presents a novel conflict-resolving neural network classifier that combines the ordering algorithm, fuzzy ARTMAP (FAM), and the dynamic decay adjustment (DDA) algorithm, into a unified framework. The hybrid ... |
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Early detection is paramount to reduce the high death rate of ovarian cancer. Unfortunately, current detection toot is not sensitive. New techniques such as deoxyribonucleic acid (DNA) micro-array and proteomics data are ... |
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A neural architecture, fuzzy ARTMAP, is considered here as an alternative to standard feedforward networks for noisy mapping tasks. It is one of a series of architectures based upon adaptive resonance theory or ART. Like ... |
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The FuzzyARTMAP algorithm is studied with respect to its usefulness for supervised chemical pattern recognition. The theory of this relatively complex artificial neural classifier is presented in detail for chemists. An ... |
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The supervised working FuzzyARTMAP pattern recognition algorithm has been applied to automated identification of post-consumer plastics by near-infrared spectroscopy (NIRS). Experimentally, a remote operating parallel ... |
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A new neural network architecture for incremental supervised learning of analog multidimensional maps is introduced. The architecture, called Gaussian ARTMAP, is a synthesis of a Gaussian classifier and an adaptive resonance ... |
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The fuzzy ARTMAP has been applied to the supervised classification of multi-spectral remotely-sensed images. This method is found to be more efficient, in terms of classification accuracy, compared to the conventional ... |
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| Abstract |
The Fuzzy ARTMAP neural network is a supervised pattern recognition method based on fuzzy adaptive resonance theory (ART). It is a promising method since Fuzzy ARTMAP is able to carry out on-line learning without forgetting ... |
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| Abstract |
Mechanical assembly by robots has traditionally depended on simple sensing systems and the robot manufacturers programming language. However, this restricts the use of robots in complex manufacturing operations. An ... |
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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 ... |
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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 ... |
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In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized ... |
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Robotic agents can greatly be benefited from the integration of perceptual learning in order to monitor and adapt to changing environments. To be effective in complex unstructured environments, robots have to perceive the ... |
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This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural ... |
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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 ... |
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This paper focuses on the evolution of Fuzzy ARTMAP neural network classifiers, using genetic algorithms, with the objective of improving generalization performance (classification accuracy of the ART network on unseen test ... |
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In this paper, we modify the fuzzy ARTMAP (FA), neural network (NN) using the Bayesian framework in order to improve its classification accuracy while simultaneously reduce its category proliferation. The proposed algorithm, ... |
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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 ... |
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Personalized information systems represent the recent effort of delivering information to users more effectively in the modern electronic age. This paper illustrates how a supervised adaptive resonance theory (ART) system, ... |
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The paper presents two neural networks based on the adaptive resonance theory (ART) for the recognition of several odors subjected to drift. The neural networks developed by Grossberg (supervised and unsupervised) have been ... |
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| Abstract |
The family of artificial neural networks based on Adaptive Resonance Theory (ART) forms a collection of distinct mathematical pattern recognition methods. The classification of sensor signals, process data analysis, spectral ... |
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A system and method is provided for monitoring the operating condition of a pump by evaluating fault data encoded in the instantaneous current of the motor driving the pump. The data is converted to a frequency spectrum ... |
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The invention provides a machine fault diagnostic system to help ensure effective equipment maintenance. The major technique used for fault diagnostics is a fault diagnostic network (FDN) which is based on a modified ARTMAP ... |
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This paper introduces Cascade ARTMAP, a system based on fuzzy ARTMAP with an addition of rule-based knowledge discovery and prior knowledge initialization, used for symbolic knowledge extraction and ... |
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This paper presents research into the application of the fuzzy ARTMAP neural network model to medical pattern classification tasks. A number of domains, both diagnostic and prognostic, are considered. Each such domain ... |
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This paper focuses on two ART architectures, the Fuzzy ART and the Fuzzy ARTMAP. Fuzzy ART is a pattern clustering machine, while Fuzzy ARTMAP is a pattern classification machine. Our study concentrates on the order ... |
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One of the properties of FAM, which is a mixed blessing, is its capacity to produce new neurons (templates) on demand to represent classification categories. This property allows FAM to automatically adapt to the database ... |
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A modified fuzzy ARTMAP neural-network-based QSPR for predicting normal boiling points, critical temperatures, and critical pressures of organic compounds was developed. Seven or eight molecular descriptors (the sum of ... |
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A new architecture, called ARTMAP, is proposed to impact a category proliferation problem present in Fuzzy ARTMAP. Under a probabilistic setting, it seeks a partition of the input space that optimizes the mutual information ... |
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In this paper we introduce a procedure, based on the max?min clustering method, that identifies a fixed order of training pattern presentation for fuzzy adaptive resonance theory mapping (ARTMAP). This procedure is referred ... |
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Self-organized maps (SOM) have been applied to analyze the similarities of chemical compounds and to select from a given pool of descriptors the smallest and more relevant subset needed to build robust QSAR models based on ... |
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The work described in this paper addresses the problems of fault diagnosis in complex multicircuit transmission systems, in particular those arising due to mutual coupling between the two parallel circuits under different ... |
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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 ... |
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An incremental, nonparametric probability estimation procedure using a variation of the Fuzzy ARTMAP (FAM) neural network is introduced. The resulted network, called Fuzzy ARTMAP with Relevance factor (FAMR), uses a ... |
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Advances in molecular classification of tumours may play a central role in cancer treatment. Here, a novel approach to genome expression pattern interpretation is described and applied to the recognition of B-cell ... |
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Fuzzy ARTMAP is a supervised learning system which includes nonlinear dynamics in the learning process. We introduce a new testing procedure which allows the system to estimate the probability of an outcome. Simulations ... |
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A nonparametric probability estimation procedure using the fuzzy ARTMAP neural network is here described. Because the procedure does not make a priori assumptions about underlying probability distributions, it yields ... |
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On a database derived from patients hospitalized with pneumonia, the authors compared the cross-validated predictions of linear discriminant analysis (LDA) to a new self-organizing supervised neural network that incorporates ... |
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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 ... |
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ARTMAP-FD extends fuzzy ARTMAP to perform familiarity discrimination. That is, the network learns to abstain from meaningless guesses on patterns not belonging to a class represented in the training set. ARTMAP-FD can also ... |
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| Abstract |
For many years, the subjects of artificial intelligence, neural networks, and fuzzy logic were developed by separate intellectual communities. This was due more, perhaps, to social and institutional barriers to ... |
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This work investigates the use of a fuzzy ARTMAP neural network for detecting cancerous cells, based on the one-class problem approach. This approach is inspired by the way human beings perform pattern recognition. We all ... |
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| Abstract |
An incremental, nonparametric probability estimation procedure using the fuzzy ARTMAP (adaptive resonance theory-supervised predictive mapping) neural network is introduced. In the slow-learning mode, fuzzy ARTMAP searches ... |
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This work proposes a new approach to signature verification. It is inspired by the human learning and the approach adopted by the expert examiner of signatures, in which an a priori knowledge of the class of forgeries is not ... |
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| Abstract |
A new neural network architecture is introduced for the recognition of pattern classes after supervised and unsupervised learning. Applications include spatio-temporal image understanding and prediction and ... |
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| Abstract |
Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP networks synthesize fuzzy logic and ART by ... |
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ART-EMAP synthesizes adaptive resonance theory (ART) and spatial and temporal evidence integration for dynamic predictive mapping (EMAP). The network extends the capabilities of fuzzy ARTMAP in four incremental stages. ... |
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The apparent dichotomy between symbolic AI processing and distributed neural processing cannot be absolute, since neural networks that capture essential features of human intelligence will also model some of the symbolic ... |
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| 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 ... |
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| Abstract |
ARTMAP is a class of neural network architectures that perform incremental supervised learning of recognition categories and multidimensional maps in response to input vectors presented in arbitrary order. The first ARTMAP ... |
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A procedure that uses fuzzy ARTMAP and K-Nearest Neighbor (K NN) categorizers to evaluate intrinsic and extrinsic speaker normalization methods is described. Each classifier is trained on preprocessed, or normalized, vowel ... |
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| Abstract |
Fuzzy ARTMAP and K-Nearest Neighbor (K-NN_ categorizers were used to evaluate intrinsic and extrinsic normalization methods by training and testing on disjoint sets of speakers of the Peterson-Barney database. Intrinsic ... |
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| Abstract |
A major national effort is underway to determine patterns of medical practice that most effectively result in favorable health outcomes. Databases arising from such effectiveness research may contain tens of thousands of ... |
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| Abstract |
A new neural network architecture is introduced for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequences of analog or binary input vectors, which may ... |
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| Abstract |
The authors compare the performance of fuzzy ARTMAP with that of learned vector quantization and back propagation on a handwritten character recognition task. Training with fuzzy ARTMAP to a fixed criterion used many fewer ... |
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| Abstract |
Fuzzy ARTMAP, one of a rapidly growing family of attentive self-organizing learning, hypothesis testing, and prediction systems that have evolved from the biological theory of cognitive information processing of which ART ... |
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| Abstract |
ARTMAP is a class of neural network architectures that employ attentional mechanisms to perform incremental supervised learning of recognition categories and multidimensional maps. The first ARTMAP system (Carpenter, ... |
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| Abstract |
How do humans rapidly recognize a scene? How can neural models capture this biological competence to achieve state-of-the-art scene classification? The ARTSCENE neural system
classifies natural scene photographs by using ... |
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This application illustrates how the fuzzy ARTMAP neural network can be used to monitor environmental changes. A benchmark problem seeks to classify regions of a Landsat image into six soil and crop classes based on images ... |
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ARTMAP-DS extends fuzzy ARTMAP to discriminate between similar inputs by discounting similarities. When two or more candidate category representations are activated by a given input, features that the candidate ... |
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The raw sensory input available to a mobile robot suffers from a variety of shortcomings. Sensor fusion can yield a percept more veridical than is available from any single sensor input. In this project, the fuzzy ARTMAP ... |
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The default ARTMAP algorithm and its parameter values specified here define a ready-to-use general-purpose neural network system for supervised learning and ... |
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| Abstract |
Principles derived from an analysis of experimental literatures in vision, speech, cortical development, and reinforcement learning, including attentional blocking and cognitive-emotional interactions, led to the ... |
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| Abstract |
According to statistics from NIH (National Institute of Health), cervical cancer is the third most common reproductive tract malignancy (ranking behind endometrium and ovary cancers) with about 13000 new case seen annually ... |
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| Abstract |
This work proposes a new approach to signature verification. It is inspired by the human learning and the approach adopted by the expert examiner of signatures, in which an a priori knowledge of the class of forgeries is not ... |
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| Abstract |
This work presents a fuzzy ARTMAP based off-line signature verification system. Compared to the conventional systems proposed thus far, the presented system is trained with genuine signatures only. Six experiments have been ... |
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| Abstract |
This paper presents a new method for the recognition of Arabic text using global features and fuzzy ARTMAP neural network. The method is divided into three major steps. The first step is digitization and pre-processing to ... |
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This paper presents a method for recognizing graphics symbols of electronic components in a database of circuit layouts. The method is based on the one-class problem approach on our ability to recognize a 2D-objects without ... |
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| 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 ... |
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| Description |
Self-Supervised ARTMAP learns about novel features from unlabeled patterns without destroying
partial knowledge previously acquired from labeled ... |
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| Description |
Complement Coding takes as input a vector of feature values, each with an associated lower and upper limit used for normalization. It normalizes each feature value and calculates its ... |
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