This paper discusses the modulation recognition for OFDM signals in different Signal to Noise Ratio (SNR) and multipath channels. In this paper, the Mel Frequency Cepstral Coefficients (MFCCs) used for feature extraction and the Support Vector Machine (SVM) as classifier or Artificial Neural Network (ANN). Simulation results indicate that the proposed feature classifier have good performances i...

Document image analysis is a major research area in pattern recognition system for identification image objects within a document and their classification. Face recognition is most widely used and efficient system in biometric. Existing methods worked on these areas of document image analysis and face recognition separately. In this paper, an attempt is made to develop a novel system to authent...

in this paper, a smart method is designed in order to classify healthy and illness ducks using their emission voice. for this purpose, firstly, the birds based on their healthy condition are divided into the different categories and then their voices are saved using a microphone and data acquisition card. gained signals were transformed from time-domain signal to frequency domain using fast fou...

Facial Expression is a key component in evaluating a person's feelings, intentions and characteristics. Facial Expression is an important part of human-computer interaction and has the potential to play an equal important role in humancomputer interaction. The aim of this paper is bring together two areas in which are Artificial Neural Network (ANN) and KNearest Neighbor (K-NN) applying for fac...

Received Dec 9, 2016 Revised Mar 27, 2017 Accepted Apr 11, 2017 The accurate land use land cover (LULC) classifications from satellite imagery are prominent for land use planning, climatic change detection and eco-environment monitoring. This paper investigates the accuracy and reliability of Support Vector Machine (SVM) classifier for classifying multispectral image of Hyderabad and its surrou...

The concept of using ANN-like approximators for estimation of dynamic system parameters is considered. It is shown that the modular, classifier-approximator architecture offers new possibilities of realtime observation point selection for optimal ANN performance in terms of minimum parameter variance.

this paper deals with the classification of cardiovascular disease for its future analysis. If future progression of the disease can be predicted earlier with proper change in medication patients treatment can be improved. Artificial neural network (ANN) is used as classifier with wavelet transform as the feature extraction for reducing data set of ECG. Hidden markov model (HMM) is used as pred...

Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested during optimum stage for maximum oil production. This paper presents the application of color vision for automated ripeness classification of oil palm FFB. Images of oil palm FFBs of type DxP Yangambi were collected and analyzed using digital image processing technique...

Artificial Neural Network (ANN) is an important tool for Pattern Recognition in Artificial Intelligence field. In this paper, we presented a hardware implementation of ANN based on modification of Boolean k-nearest neighbor (BKNN) classifier proposed by Gazula and Kabuka. BKNN is a kind of supervised classifier using Boolean Neural Network, which has binary inputs and outputs, integer weights, ...