ART 2 / Fuzzy ART

Adaptive Resonance Theory (ART) neural network supporting continuous (analog) inputs.


Articles & Tech Transfers


An Alternative Evaluation of FMEA: Fuzzy ART Algorithm
Abstract Failure Mode and Effects Analysis (F MEA) is a technique used in the manufacturing industry to improve production quality and productivity. It is a method that evaluates possible failures in the system, design, process or ...

Fault diagnosis of pneumatic systems with artificial neural network algorithms
Abstract Pneumatic systems repeat the identical programmed sequence during their operation. The data was collected when the pneumatic system worked perfectly and had some faults including empty magazine, zero vacuum, inappropriate ...

dFasArt: Dynamic neural processing in FasArt model
Abstract The temporal character of the input is, generally, not taken into account in the neural models. This paper presents an extension of the FasArt model focused on the treatment of temporal signals. FasArt model is proposed as ...

Critical Motion Detection of Nearby Moving Vehicles in a Vision-Based Driver-Assistance System
Abstract Driving always involves risk. Various means have been proposed to reduce the risk. Critical motion detection of nearby moving vehicles is one of the important means of preventing accidents. In this paper, a computational ...

Computational Intelligence Meets the NetFlix Prize
Abstract The NetFlix Prize is a research contest that will award $1 Million to the first group to improve NetFlix's movie recommendation system by 10%. Contestants are given a dataset containing the movie rating histories of ...

Data Mining System for Biochemical Analysis in Experimental Physiology
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 ...

A neural network method for detection of obstructive sleep apnea and narcolepsy based on pupil size and EEG
Abstract Electroencephalogram (EEG) is able to indicate states of mental activity ranging from concentrated cognitive efforts to sleepiness. Such mental activity can be reflected by EEG energy. In particular, intrusion of EEG theta ...

An intelligent ballistocardiographic chair using a novel SF-ART neural network and biorthogonal wavelets
Abstract 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 ...

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 ...

Incremental clustering of mixed data based on distance hierarchy
Abstract Clustering is an important function in data mining. Its typical application includes the analysis of consumer s materials. Adaptive resonance theory network (ART) is very popular in the unsupervised neural network. Type I ...

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 ...

TOWARDS AN ART BASED MATHEMATICAL EDITOR, THAT USES ONLINE HANDWRITTEN SYMBOL RECOGNITION
Abstract A new mathematical editor, based on the recognition of run-on discrete handwritten symbols, is proposed. The tested laboratory prototype of the system, modular and adaptable to the user habits and site requirements, uses a ...

DETECTION OF TOOL FAILURE IN END MILLING WITH WAVELET TRANSFORMATIONS AND NEURAL NETWORKS (WT-NN)
Abstract Detection of tool failure is very important in automated manufacturing. In this study, tool failure detection was conducted in two steps by using Wavelet Transformations and Neural Networks (WT-NN). In the first step, data ...

ART-based multiple neural networks for monitoring offshore platforms
Abstract A novel scheme using artificial neural networks to automate the vibration monitoring method of detecting the occurrence and location of damage in offshore jacket platforms is presented. A multiple neural network system is ...

Performance enhancement for fuzzy adaptive resonance theory (ART) neural networks
Abstract A modified fuzzy adaptive resonance theory neural network (ART) is used as a classifier for a texture recognition system. The system consists of a wavelet based low level feature detector and a high level ART classifier. The ...

On-line Chinese character recognition using ART-based stroke classification
Abstract This paper proposes an on-line Chinese character recognition method using Adaptive Resonance Theory (ART) based stroke classification. Strokes, primitive components of Chinese characters, are usually warped into a cursive ...

Using ART2 networks to deduce flow velocities
Abstract A novel algorithm for obtaining flow velocity vectors using ART2 networks (based on adaptive resonance theory) is presented. The method involves tracking the movement of groups of seeding particles in a fluid space through ...

Exact ART: A complete implementation of an ART network
Abstract In this article we introduce a continuous time implementation of adaptive resonance theory (ART). ART designed by Grossberg concerns neural networks that self-organize stable pattern recognition categories of arbitrary ...

Application of artificial neural networks for the development of a signal monitoring system
Abstract A prototype of a Signal Monitoring System (SMS) utilizing artificial neural networks is developed in this work. The prototype system is unique in: 1) its utilization of state-of-the-art technology in pattern recognition such ...

Feature recognition using ART2: A self-organizing neural network
Abstract A self-organizing neural network, ART2, based on adaptive resonance theory (ART), is applied to the problem of feature recognition from a boundary representation (B-rep) solid model. A modified face score vector calculation ...

Wavelet-based feature-adaptive adaptive resonance theory neural network for texture identification
Abstract A new method of texture classification comprising two processing stages, namely a low-level evolutionary feature extraction based on Gabor wavelets and a high-level neural network based pattern recognition, is proposed. The ...

Using neural networks for the diagnosis of localized defects in ball bearings
Abstract Two neural network based approaches, a multilayered feed forward neural network trained with supervised Error Back Propagation technique and an unsupervised Adaptive Resonance Theory-2 (ART2) based neural network were used ...

Comparative analysis of fuzzy ART and ART-2A network clustering performance
Abstract Adaptive resonance theory (ART) describes a family of self-organizing neural networks, capable of clustering arbitrary sequences of input patterns into stable recognition codes. Many different types of ART-networks have been ...

Application of wavelets and neural networks to diagnostic system development, 1, feature extraction
Abstract An integrated framework for process monitoring and diagnosis is presented which combines wavelets for feature extraction from dynamic transient signals and an unsupervised neural network for identification of operational ...

Properties of learning of a Fuzzy ART Variant
Abstract This paper discusses a variation of the Fuzzy ART algorithm referred to as the Fuzzy ART Variant. The Fuzzy ART Variant is a Fuzzy ART algorithm that uses a very large choice parameter value. Based on the geometrical ...

Generalization, discrimination, and multiple categorization using adaptive resonance theory
Abstract The internal competition between categories in the adaptive resonance theory (ART) neural model can be biased by replacing the original choice function by one that contains an attentional tuning parameter under external ...

Intelligent tool wear identification based on optical scattering image and hybrid artificial intelligence techniques
Abstract Tool wear monitoring is crucial for an automated machining system to maintain consistent quality of machined parts and prevent damage to the parts during the machining operation. A vision-based approach is presented for tool ...

Self-organizing arterial pressure pulse classification using neural networks: theoretical considerations and clinical applicability
Abstract A self-organizing classification system for the arterial pressure pulse based on the ART2 (adaptive resonance theory) network was developed. The system consists of a preprocessor and an ART2 recognition network. The ...

Determining temporal pattern of community dynamics by using unsupervised learning algorithms
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 ...

Classification of malignant and benign masses based on hybrid ART2LDA approach
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 ...

Fuzzy lattice neurocomputing (FLN) models
Abstract In this work it is shown how fuzzy lattice neurocomputing (FLN) emerges as a connectionist paradigm in the framework of fuzzy lattices (FL-framework) whose advantages include the capacity to deal rigorously with: disparate ...

Learning from noisy information in FasArt and FasBack neuro-fuzzy systems
Abstract Neuro-fuzzy systems have been in the focus of recent research as a solution to jointly exploit the main features of fuzzy logic systems and neural networks. Within the application literature, neuro-fuzzy systems can be found ...

A Modified Fuzzy ART for Soft Document Clustering
Abstract Document clustering is a very useful application in recent days especially with the advent of the World Wide Web. Most of the existing document clustering algorithms either produce clusters of poor quality or are highly ...

A novel approach to the derivation of fuzzy membership functions using the Falcon-MART architecture
Abstract A fuzzy neural network, Falcon-MART, is proposed in this paper. This is a modification of the original Falcon-ART architecture. Both Falcon-ART and Falcon-MART are fuzzy neural networks that can be used as fuzzy controllers ...

Vector quantization of images using modified adaptive resonance algorithm for hierarchical clustering
Abstract Most neural-network (NN) algorithms used for the purpose of vector quantization (VQ) focus on the mean squared error minimization within the reference- or code-vector space. This feature frequently causes increased entropy ...

Unsupervised adaptive resonance theory neural networks for control chart pattern recognition
Abstract This paper describes the use of unsupervised adaptive resonance theory ART2 neural networks for recognizing patterns in statistical process control charts. To improve the classification accuracy, three schemes are proposed. ...

NeuroFAST: On-line neuro-fuzzy ART-based structure and parameter learning TSK model
Abstract NeuroFAST is an on-line fuzzy modeling learning algorithm, featuring high function approximation accuracy and fast convergence. It is based on a first-order Takagi-Sugeno-Kang (TSK) model, where the consequence part of each ...

Mining a Web citation database for document clustering
Abstract The World Wide Web has become an important medium for disseminating scientific publications. Many publications are now made available over the Web. However, existing search engines are ineffective in searching these ...

Constructive feedforward ART clustering networks - Part I
Abstract 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 ...

Constructive feedforward ART clustering networks - Part II
Abstract Part I of this paper defines the class of constructive unsupervised on-line learning simplified adaptive resonance theory (SART) clustering networks. Proposed instances of class SART are the symmetric Fuzzy ART (S-Fuzzy ART) ...

A strategy for acquiring customer requirement patterns using laddering technique and ART2 neural network
Abstract With the increasing interest and emphasis on customer demands in new product development, customer requirements elicitation (CRE) and evaluation have secured a crucial position in the early stage of product ...

An ART-based fuzzy controller for the adaptive navigation of a quadruped robot
Abstract An adaptive-resonance theory (ART)-based fuzzy controller is presented for the adaptive navigation of a quadruped robot in cluttered environments, by incorporating the capability of ART in stable category recognition into ...

Screening of stress enhancer based on analysis of gene expression profiles: Enhancement of hyperthermia-induced tumor necrosis by an MMP-3 inhibitor
Abstract To improve the therapeutic benefit of hyperthermia, we examined changes of global gene expression after heat shock using DNA microarrays consisting of 12 814 clones. HeLa cells were treated for 1 h at 44degreesC and RNA was ...

Roles and representations of systematic fine phonetic detail in speech understanding
Abstract This paper aims to show how we can make progress in elucidating how people understand speech by changing our focus of inquiry from abstraction of formal units of linguistic analysis to a detailed analysis of global aspects ...

Inference of common genetic network using fuzzy adaptive resonance theory associated matrix methods
Abstract Inferring genetic networks from gene expression data is the most challenging work in the postgenomic era. However, most studies tend to show their genetic network inference ability by using artificial data. Here, we ...

On-line tool breakage monitoring in turning
Abstract Acoustic emission (AE) and motor power sensors were used to detect the tool breakage in turning. Time-frequency analysis was used to process different AE signals emitted from the cutting process (normal cutting condition, ...

Performance of Fuzzy ART neural network and hierarchical clustering for part-machine grouping based on operation sequences
Abstract The problem context for this study is one of identifying families of parts having a similar sequence of operations. This is a prerequisite for the implementation of cellular manufacturing, group technology, just-in-time ...

Model-based fault detection and isolation method using ART2 neural network
Abstract This article presents a model-based fault diagnosis method to detect and isolate faults in the robot arm control system. The proposed algorithm is composed functionally of three main parts: parameter estimation, fault ...

A syntactic methodology for automatic diagnosis by analysis of continuous time measurements using hierarchical signal representations
Abstract In this paper, we present a methodology for automatic diagnosis of systems characterized by continuous signals. For each condition considered, the methodology requires the development of an alphabet of signal primitives, and ...

Manufacturing quality control by means of a Fuzzy ART network trained on natural process data
Abstract In order to produce products with constant quality, manufacturing systems need to be monitored for any unnatural deviations in the state of the process. Control charts have an important role in solving quality control ...

A clustering fuzzy approach for image segmentation
Abstract Segmentation is a fundamental step in image description or classification. In recent years, several computational models have been used to implement segmentation methods but without establishing a single analytic solution. ...

Trichromatic sorting of in vitro regenerated plants of gladiolus using adaptive resonance theory
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 ...

Clustering in wavelet domain: A multiresolution ART network for anomaly detection
Abstract A method for process fault detection is presented, based on the integration of multiscale signal representation and scale-specific clustering-based diagnosis. Previous work has demonstrated the utility of our multiscale ...

Adaptive Resonance Theory-based neural algorithms for manufacturing process quality control
Abstract The demand for quality products in industry is continuously increasing. To produce products with consistent quality, manufacturing systems need to be closely monitored for any unnatural deviation in the state of the process. ...

An automatic road sign recognition system based on a computational model of human recognition processing
Abstract This paper presents an automatic road sign detection and recognition system that is based on a computational model of human visual recognition processing. Road signs are typically placed either by the roadside or above ...

A hybrid neural network model for noisy data regression
Abstract A hybrid neural network model, based on the fusion of fuzzy adaptive resonance theory (FA ART) and the general regression neural network (GRNN), is proposed in this paper. Both FA and the GRNN are incremental learning ...

Incremental communication for adaptive resonance theory networks
Abstract We have proposed earlier the incremental internode communication method to reduce the communication cost as well as the time of the learning process in artificial neural netwofrks (ANNs). In this paper, the limited precision ...

Time-course data analysis of gene expression profiles reveals purR regulon concerns in organic solvent tolerance in Escherichia coli
Abstract A time-course gene-expression profile was generated for Escherichia coli TK31 when it was exposed to an organic solvent mixture, and classified by fuzzy adaptive resonance theory (Fuzzy ART). It was found that the purR ...

A new ART-counterpropagation neural network for solving a forecasting problem
Abstract This study presents a novel Adaptive resonance theory-Counterpropagation neural network (ART-CPN) for solving forecasting problems. The network is based on the ART concept and the CPN learning algorithm for constructing the ...

Fuzzy-ART based adaptive digital watermarking scheme
Abstract In this paper, a novel transform domain digital watermarking scheme that uses visually meaningful binary image as watermark has been developed. The method embeds the watermark information adaptively with localized embedding ...

Fuzzy ART neural network algorithm for classifying the power system faults
Abstract This paper introduces advanced pattern recognition algorithm for classifying the transmission line faults, based on combined use of neural network and fuzzy logic. The approach utilizes self-organized, supervised Adaptive ...

Integration of ART2 neural network and genetic K-means algorithm for analyzing Web browsing paths in electronic commerce
Abstract Neural networks and genetic algorithms are useful for clustering analysis in data mining. Artificial neural networks (ANNs) and genetic algorithms (GAs) have been applied in many areas with very promising results. Thus, this ...

Understanding ART-based neural algorithms as statistical tools for manufacturing process quality control
Abstract Neural networks have recently received a great deal of attention in the field of manufacturing process quality control, where statistical techniques have traditionally been used. In this paper, a neural-based procedure for ...

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 ...

Integrated clustering approach to developing technology for functional feature and engineering specification-based reference design retrieval
Abstract Engineering design is a complex activity, and is heavily reliant on the know-how of engineering designers. Hence, capturing, storing, and reusing design information, design intent, and underlining design knowledge to support ...

Hybrid feature vector extraction in unsupervised learning neural classifier
Abstract Feature extraction and selection method as a preliminary stage of heart rate variability (HRV) signals unsupervised learning neural classifier is presented. Multi-domain, mixed new feature vector is created from time, ...

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 ...

Automated categorization of bioacoustic signals: Avoiding perceptual pitfalls
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, ...

Transformations in machining. Part 1. enhancement of wavelet transformation neural network (WT-NN) combination with a preprocessor
Abstract Properly selected transformation methods obtain the most significant characteristics of metal cutting data efficiently and simplify the classification. Wavelet Transformation (WT) and Neural Networks (NN) combination was ...

Incorporating PCA and fuzzy-ART techniques into achieve organism classification based on codon usage consideration
Abstract To recognize the DNA sequence and mine the hidden information to achieve the classification of organisms are viewed as a difficult work to biologists. As we know, the amino acids are the basic elements to construct DNA. ...

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 ...

Classification of intramural metastases and lymph node metastases of esophageal cancer from gene expression based on boosting and projective adaptive resonance theory
Abstract Esophageal cancer is a well-known cancer with poorer prognosis than other cancers. An optimal and individualized treatment protocol based on accurate diagnosis is urgently needed to improve the treatment of cancer patients. ...

ART 2 - an unsupervised neural network for PD pattern recognition and classification
Abstract This paper introduces a method of classifying partial discharges of unknown origin. The innovative trend of using Artificial Neural Network (ANN) towards classification of Partial Discharge (PD) patterns is cogent and ...

Neural networks for animal science applications: Two case studies
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 ...

Prune-able fuzzy ART neural architecture for robot map learning and navigation in dynamic environments
Abstract Mobile robots must be able to build their own maps to navigate in unknown worlds. Expanding a previously proposed method based on the fuzzy ART neural architecture (FARTNA), this paper introduces a new online method for ...

RT-UNNID: A practical solution to real-time network-based intrusion detection using unsupervised neural networks
Abstract With the growing rate of network attacks, intelligent methods for detecting new attacks have attracted increasing interest. The RT-UNNID system, introduced in this paper, is one such system, capable of intelligent real-time ...

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 ...

Adaptive anomaly detection with evolving connectionist systems
Abstract Anomaly detection holds great potential for detecting previously unknown attacks. In order to be effective in a practical environment, anomaly detection systems have to be capable of online learning and handling concept ...

A real time fault analysis tool for monitoring operation of transmission line protective relay
Abstract This paper proposes an integrated real time fault analysis tool for transmission line. The two primary techniques used in the fault analysis tool, fuzzy adaptive resonance theory (ART) neural network and synchronized ...

An approach based on the Adaptive Resonance Theory for analysing the viability of recommender systems in a citizen Web portal
Abstract This paper proposes a methodology to optimize the future accuracy of a collaborative recommender application in a citizen Web portal. There are four stages namely, user modeling, benchmarking of clustering algorithms, ...

Soliciting customer requirements for product redesign based on picture sorts and ART2 neural network
Abstract Design knowledge acquisition plays an extremely important role in new product conceptualization and product redesign. This study aims at facilitating the effectiveness of product redesign activities. It involves two ...

Photometric clustering of regenerated plants of gladiolus by neural networks and its biological validation
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 ...

The application of clustering analysis for the critical areas on TFT-LCD panel
Abstract For thin film transistor-liquid crystal displays (TFT-LCD) factories in Taiwan, yield performance had become as an important competitiveness determinant during the competitive environment. As we known, the market for LCDs ...

A Self-Organizational Management Network Based on Adaptive Resonance Theory
Abstract This paper presents an organizational network for product configuration management within the context of Virtual Enterprise. Actors, from high level strategy making actors to low level physical devices, can advertise their ...

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 ...

Odor discrimination using adaptive resonance theory
Abstract 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 ...

Modeling developmental transitions in adaptive resonance theory
Abstract Neural networks are applied to a theoretical subject in developmental psychology: modeling developmental transitions. Two issues that are involved will be discussed: discontinuities and acquiring qualitatively new knowledge. ...

Abnormality diagnosis of GIS using adaptive resonance theory
Abstract The paper presents an artificial neural network (ANN) approach using ART2 (Adaptive Resonance Theory 2) to a diagnostic system for gas insulated switchgear (GIS). To begin with, the authors show the background of abnormality ...

Construction of robust prognostic predictors by using projective adaptive resonance theory as a gene filtering method
Abstract We applied projective adaptive resonance theory (PART) to gene screening for DNA microarray data. Genes selected by PART were subjected to our FNN-SWEEP modeling method for the construction of a cancer class prediction ...

VLSI Implementation of Fuzzy Adaptive Resonance and Learning Vector Quantization
Abstract We present a mixed-mode VLSI chip performing unsupervised clustering and classification, implementing models of fuzzy adaptive resonance theory (ART) and learning vector quantization (LVQ), and extending to variants such as ...

Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system
Abstract Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies ...

Detection of pump cavitation/blockage and seal failure via current signature analysis
Abstract 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 ...

DNA sequence analysis using hierarchical ART-based classification networks
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 ...

Rapid category learning and recognition system
Abstract An improved ART2 network provides fast and intermediate learning. The network combines analog and binary coding functions. The analog portion encodes the recent past while the binary portion retains the distant past. LTM ...

Hierarchical pattern recognition system with variable selection weights
Abstract In a pattern recognition system, input signals are applied to a short term feature representation field of nodes. A pattern from the short term feature representation field selects at least one category node in a category ...

Classification method and apparatus based on boosting and pruning of multiple classifiers
Abstract A boosting and pruning system and method for utilizing a plurality of neural networks, preferably those based on adaptive resonance theory (ART), in order to increase pattern classification accuracy is presented. The method ...

Neural network based analysis system for vibration analysis and condition monitoring
Abstract A system and a method for tracking long term performance of a vibrating body such as a gas turbine, includes a vibration sensor who time domain outputs are transformed to the frequency domain, using a fast Fourier transform ...

Order of Search in Fuzzy ART and Fuzzy ARTMAP: Effect of the Choice Parameter
Abstract 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 ...

Fuzzy LAPART Supervised Learning Through Inferencing for Stable Category Recognition
Abstract Fuzzy LAPART (laterally primed adaptive resonance theory), a neural network architecture for supervised learning through logical inferencing, is introduced with fast and slow learning algorithms and match tracking ...


Software


Fuzzy ARTMAP
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.


  1. Stripes benchmark (sparse)

  2. Stripes benchmark

...

Complement Coding
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 ...