In this paper we are working on the Neural Network based classifier that solves the classification problem. The paper describes the multilayer perception approach to describe the neural network architecture. For this classifier we use the Fisher’s Iris Database (Fisher, 1936) available in MATLAB and on the Internet. This database is the preprocessed and is the best database in the pattern recog...

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-toNoise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify ...

This paper describes the design and modeling of an artificial neural network (ANN) classifier using VHDL. This classifier is targeted primarily to classify the six different types of power quality disturbance. The high level architecture comprises of a control unit and a neural network datapath. The control unit is further divided into five interconnected sub modules: bus master, ram, pseudo ra...

Classifier systems are machine learning systems incotporating a genetic algorithm as the learning mechanism. Although they respond to inputs that neural networks can respond to, their internal structure, representation fonnalisms, and learning mechanisms differ marlcedly from those employed by neural network researchers in the same sorts of domains. As a result, one might conclude that these tw...

In the present study, the effectiveness of the adaptive resonance theory neural network (ART2) is illustrated in the context of automatic classification of abnormal brain tumor images. Abnormal images from four different classes namely metastase, meningioma, glioma and astrocytoma have been used in this work. Initially, textural features are extracted from these images. An extensive feature sel...

Background To detect antinuclear antibodies (ANA) on the blood’s patients is a mostly used technique to diagnose immunologic diseases. The Indirect Immunofluorescence method (IIF) generates images with ANA patterns them and commonly by immunology laboratories around world. Those are documented in International Consensus of Patterns (ICAP) there 29 at present, split into three main groups: Nucle...

Two reject mechanisms are compared using a massively parallel character recognition system implemented at NIST. The recognition system was designed to study the feasibility of automatically recognizing hand-printed text in a loosely constrained environment. The first method is a simple scalar threshold on the output activation of the winning neurode from the character classifier network. The se...

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, ...

The explosive growth of image data leads to the research and development of image content searching and indexing systems. Image annotation systems aim at annotating automatically animage with some controlled keywords that can be used for indexing and retrieval of images. This paper presents a comparative evaluation of the image content annotation system by using the multilayer neural networks a...