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Hilbert Transform (HT) and Multi Wavelet Transform (MWT) has been used to recognize the same frequency harmonics that occur in the brain with the Steady State Visual Evoked Potentials(SSVEP). In this study, harmonics of certain frequencies in brain are used which are detected by SSVEP and visual stimulus potentials to be used in Robot Arm Control. This stimulus has been made using shapes of box that...
Classification of signals acquired by condition monitoring systems for automotive application is becoming increasingly important. The work presented in this paper is motivated by a real-life classification challenge organized by Ford. Data samples from an automotive subsystem were collected. A classifier is designed to robustly isolate the different types of problems, by analyzing the acquired signals...
The objective of this paper is to evaluate the classification performance of several feature extraction and classification methods for exotic wood texture images as dataset. The Gray Level Co-occurrence Matrix, Local Binary Patterns, Wavelet, Ranklet, Granulometry, and Laws' Masks will be used to extract features from the images. The extracted features are then fed into five classification techniques:...
An automatic target recognition (ATR) system based on rough set-support vector machine (RS-SVM) for SAR targets is proposed in this paper. The system combines the strong feature selection ability of rough set (RS) with the excellent classification ability of SVM together. The wavelet invariant moments firstly are extracted, then selected by using forward greedy numeral attribute reduction algorithm...
With development of information and communication technology, data transmission becomes more critical day by day. Higher security for transmitting data is especially required. Therefore; we designed a new method to transmit data on the phone line where there is no speech signal on it. Statistic investigations in one communication center in Iran show that there is about 57% non-speech signal on the...
The emergence of digital music in the Internet calls for a reliable real-time tool to analyze and properly categorize them for the users. To incorporate content or genre queries in Web searches, audio content analysis and classification is imperative. This paper proposes a set of audio content features and a parallel neural network architecture that addresses the task of automated content based audio...
The wavelet-based feature extraction algorithms have been developed to explore the useful information for the hyperspectral image classification. On the other hand, the idea of using artificial neural network (ANNs) has also proved useful for hyperspectral image classification. To combine the advantages of ANNs with wavelet-based feature extraction methods, the wavelet network (WN) has been proposed...
In this paper we present classification of the thermal images in order to discriminate healthy and pathological cases during breast cancer screening. Different image features and approaches for data reduction and classification have been used. The most promised method was based on wavelet transformation and nonlinear neural network classifier.
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