Search Results - (( discrete extraction method algorithm ) OR ( based optimization method algorithm ))
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Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network
Published 2023“…This proposed model will be employed in the Improved Reverse Analysis method to extract the relationship between various fields of real-life data sets based on logical representation. …”
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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3
A new ant based rule extraction algorithm for web classification
Published 2011“…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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Monograph -
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Discrete wavelet packet transform for electroencephalogram based valence-arousal emotion recognition
Published 2015“…The aim of this study is to discover the feature extraction method and the combination of electrode channels that optimally implements EEG-based valencearousal emotion recognition. …”
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Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…As a result,it will first introduce the theories about the feature extraction and the basic principles on how feature points can act as locating resynchronization between watermark insertion and extraction discussed in detail.Subsequently,it will present several content-based watermark embedding and extraction methods which can be directly implemented based on the synchronization scheme.Further detailed watermarking schemes which combine feature regions extraction with counter propagation neural network-based watermarks synapses memorization are then presented.The performance of watermarking schemes based on framework of feature point shows the following advantages:a)Good imperceptibility. …”
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6
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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7
P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…Meanwhile the new approaches in channels selection methods help the algorithms for convenient online usage.…”
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8
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues
Published 2024“…The total genomic DNA was extracted from the biopsy samples by utilizing a comprehensive kit to ensure optimal microbial DNA recovery. …”
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Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model
Published 2020“…Detecting the change in sleep stages is a complex process and requires the expertise of a neurologist. Features can be extracted by three fractal descriptors, Lyapunov exponent and cumulatively discrete wavelet transform. …”
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Conference or Workshop Item -
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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FACE CLASSIFICATION FOR AUTHENTICATION APPROACH BY USING WAVELET TRANSFORM AND STATISTICAL FEATURES SELECTION
Published 2011“…In the last method, the Modified K-Means Algorithm was used to remove the non-face regions in the input image. …”
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14
Fault Detection using Dynamic Parity Space Approach
Published 2012“…Dynamic Parity Space Approach was studied for a discrete state-space model. Important data will be extracted using this approach especially for residual generation which is the backbones of FDI analysis. …”
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Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The motor features are extracted through the proposed Discrete Wavelet Transform (DWT) based analysis method, while the wavelet inlet acts as an expert tool to adapt the right controller in accordance with the fault type. …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…Othman present a comprehensive method based on two-layer multiclass classifiers. …”
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Monograph -
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network
Published 2022“…Besides, the multi-dimensional conditional mutual information method was used to extract the frequency band features of the EEG data. …”
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Electrocardiogram based heart disease diagnosis using artificial intelligence
Published 2015“…After noise removal, the data from the ECG is to be acquired; for this purpose a method is devised based on DWT. Third stage is the features extraction; proposed a special domain based on DWT to extract diagnostic information from the ECG signal. …”
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