Search Results - (( data decomposition based algorithm ) OR ( java implication force algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The proposed method uses a rank accuracy estimation model to decide the rank-1 value to be applied for the decomposition. Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. …”
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Recursive Subspace Identification Algorithm Using The Propagator Based Method
Published 2017“…Subspace model identification (SMI) method is the effective method in identifying dynamic state space linear multivariable systems and it can be obtained directly from the input and output data. Basically, subspace identifications are based on algorithms from numerical algebras which are the QR decomposition and Singular Value Decomposition (SVD). …”
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Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system
Published 2006“…Therefore in this part QR decomposition algorithm has been investigated as a solution. …”
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Soft Set Decision/Forecasting System Based on Hybrid Parameter Reduction Algorithm
Published 2017“…Additionally, data decomposition based on previous algorithms could not achieve better parameter reduction with available domain space. …”
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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Optimization and Decomposition Methods in Network Traffic Prediction Model: A Review and Discussion
Published 2020“…This article discusses past network traffic prediction research and critically examines the optimization and decomposition technologies used in the model, lists the model parameter structure based on the research methodology, the data set used, the evaluation criteria and so on. …”
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Improving Time Series Models Prediction Based On Empirical Mode Decomposition Using Stock Market Data
Published 2021“…Therefore, there is the research scope to search for better methods to improve forecast accuracy obtainable from the traditional methods by applying advanced approaches. Empirical mode decomposition (EMD), a very essentially important part of Hilbert-Huang transforms (HHT) is a very adaptive decomposition algorithm to view data from granular and different time scales. …”
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An enhanced soft set data reduction using decision partition order technique
Published 2017“…The decomposition scenario in Rose’s and Kumar’s algorithms detects the reduction, but could not obtain the optimal decision. …”
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Optimization of medical image steganography using n-decomposition genetic algorithm
Published 2023“…To overcome these limitations, this study proposes a technique known as an n-decomposition genetic algorithm. This algorithm uses a variable-length search to identify the best location to embed the secret message by incorporating constraints to avoid local minimum traps. …”
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The AGEB algorithm for solving the heat equation in three space dimensions and its parallelization using PVM
Published 2023“…In this paper, a new algorithm in the class of the AGE method based on the Brian variant (AGEB) of the ADI is developed to solve the heat equation in 3 space dimensions. …”
Conference Paper -
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture
Published 2010“…It is shown that the computational complexity of proposed FAST-QR detection algorithm is approximately 48 % lower than the conventional QR decomposition detection algorithm. …”
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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction
Published 2021“…Given this context, this paper proposes a network traffic prediction mechanism based on optimized Variational Mode Decomposition (VMD) and Integrated Extreme Learning Machine (ELM). …”
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A survey on signal processing methods in fiber optic sensor for oxidized carbon steel
Published 2019“…The two algorithms are the Empirical Mode Decomposition and the Ensemble Empirical Mode Decomposition. …”
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A survey on signal processing methods in fiber optic sensor for oxidized carbon steel
Published 2019“…The two algorithms are the Empirical Mode Decomposition and the Ensemble Empirical Mode Decomposition. …”
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A Comparison Of The Different Algorithms For Essential Tremor And Parkinson’s Disease Tremor Differentiation Based On Hand Tremor
Published 2018“…Four different types of tremor classification algorithms, namely the Tremor Stability Index (TSI), Mean Harmonic Peak Power (MHPP), Relative Energy (RE) and Empirical Mode Decomposition – Singular Value Decomposition (EMD-SVD) analysis had been tested with 153 postural tremor recordings and 154 rest tremor recordings collected from ET and PD patients. …”
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Monograph -
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Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…One of the most promising approaches is based on optimal inverse Xltering followed by fitting an autoregressive moving average ( A M ) model to the deconvolved data so that its AR parameters are determined by solving high order Yule- Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm. …”
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Proceeding Paper -
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EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method
Published 2018“…Therefore, in this study a coupled Multivariate Empirical Mode Decomposition (MEMD) with embedded automated artifact remover algorithm and inverse solution method is proposed. …”
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HAPTIC VISUALIZATION USING VISUAL TEXTURE INFORMATION
Published 2011“…Wavelet decomposition is utilized to extract data information from texture data. …”
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Least Square QR Decomposition Method for Solving the Inverse Problem in Functional Near Infra-Red Spectroscopy
Published 2021“…In this paper, the least square QR decomposition (LSQR) method for solving the inverse problem has been implemented for real fNIRs data based on working memory (WM). …”
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