GFAM: Evolving Fuzzy ARTMAP neural networks
نویسندگان
چکیده
منابع مشابه
GFAM: Evolving Fuzzy ARTMAP Neural Networks
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 data) and alleviating the ART category proliferation problem (the problem of creating more than necessary ART network categories to solve a classification problem). We refer...
متن کاملm-GFAM: An elegant approach to genetically optimize Fuzzy ARTMAP Neural Network Architectures
Adaptive Resonance Theory (ART) neural network architectures, such as Fuzzy ARTMAP (FAM), have solved successfully a variety of classification problems. However, FAM suffers from an inherent problem that of creating larger architectures than it is necessary to solve the problem at hand (referred to as the ART category proliferation problem). This problem is especially amplified for classificati...
متن کاملClassification of Noisy Signals Using Fuzzy ARTMAP Neural Networks
This paper describes an approach to classification of noisy signals using a technique based on the fuzzy ARTMAP neural network (FAMNN). The proposed method is a modification of the testing phase of the fuzzy ARTMAP that exhibits superior generalization performance compared to the generalization performance of the standard fuzzy ARTMAP in the presence of noise. An application to textured gray-sc...
متن کاملHybrid Artmap Neural Networks (hart)
In order to reduce the effect of the category proliferation phenomenon in Fuzzy ARTMAP (FAM) and in ellipsoidal ARTMAP (EAM) architectures, The genetic algorithms were used to evolve networks of both architectures called GFAM and GEAM [3][4]. The results were very promising and the category proliferation (CP) phenomenon was minimized in most of the experiments, however, the author noticed that ...
متن کاملImage Upscaling and Fuzzy ARTMAP Neural Network
In Image upscaling, a higher resolution image is processed from an available low resolution image. There are numerous scenarios and applications where image upscaling is required and performed. The paper proposes a simple image scaling algorithm and implements it with a fuzzy variant of the supervised ART neural network, ARTMAP. The method has been compared with nearest neighbor interpolation, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Networks
سال: 2007
ISSN: 0893-6080
DOI: 10.1016/j.neunet.2007.05.006