Search Results - ((linear algorithm) OR (means algorithm))

Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

“…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
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Modeling of widely-linear quaternion valued systems using hypercomplex algorithms by Mohammed, Haydar Imad, Hashim, Fazirulhisyam, Che Ujang, Che Ahmad Bukhari

“…The data-driven optimal modeling and identification of widely-linear quaternion-valued synthetic systems is achieved by using a quaternion-valued gradient based algorithms. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…The objective of this paper is to investigate how the parameters behave with a measurement criterion for feature selection, that is, the total error reduction ratio (TERR). The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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A Stochastic Total Least Squares Solution of Adaptive Filtering Problem by Javed, Shazia, Ahmad, Noor Atinah

“…The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. …”
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Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

“…The NLFXLMS algorithm requires an exact copy of the linear and nonlinear models of the secondary path. …”
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ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION by MUBARAK MOHMMED, HUSSAM ALHAJ

“…On the other hand, Least Mean Square (LMS) algorithm is known for its ease of structure, computation and simplicity. …”
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Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

“…The performance of these algorithms is usually compared with the standard linear filtered-x least mean square (FXLMS) algorithm. …”
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Adaptive beamforming with 16 element linear array using MaxSIR and MMSE algorithms by Islam, Md. Rafiqul, Hafriz, Fahmy, Norfauzi, Muhammad

“…Maximum Signal-to-Interference Ratio (MaxSIR) and Minimum Mean Square Error (MMSE) beamforming algorithms were investigated using 16 elements linear array antenna. …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

“…Among the hybrid models, in terms of accuracy, the best optimisation algorithm at station 1K06 was the AMFO while the best optimisation algorithm at station 1K07 was the HPSOGA. …”
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Clustering Spatial Data Using a Kernel-Based Algorithm by Awan, A. Majid, Md. Sap, Mohd. Noor

“…Finally, we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering spatial data as a case study. …”
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Cryptographic Algorithm Using Matrix Inversion as Data Protection by Zirra, Peter B., Wajiga, G.M.

“…The algorithms were tested with samples of real data and the result practically demonstrated how systems of non-linear equations turned into linear equations are indeed of relevance in providing strong and complex encryption and decryption keys to protect sensitive information in store or in transit via unsecure channels. …”
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Dynamic determinant matrix-based block cipher algorithm by Juremi, Julia

“…For the avalanche effect analysis, the DDBC algorithm shows that most of the correlation values tested on the proposed determinant s-boxes and the RotateSwapDeterminant function are near to 0 which indicate a strong positive (or negative) non-linear relationship which means the DDBC algorithm has a high confusion property. …”
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

“…Filtered-X least mean square (FXLMS) control algorithm is a conventional algorithm employed to cancel the noise in linear environment. …”
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Enhanced Automated Framework For Cattle Tracking And Classification by Williams, Bello Rotimi

“…An enhanced object tracking algorithm (PFtmM) that integrates enhanced particle filter algorithm (PFtm) with mean-shift tracker (M) is proposed and deployed as first step to address the problems arise due to occurrence of occlusion and non-linear movement of cow objects in video. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. Under certain assumptions, the OLS estimates are the best linear unbiased estimates. …”
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Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network by Md Akib, Afif, Saad, Nordin, Asirvadam, Vijanth

“…Relative mass released of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithms for updating the linear weight. Radial basis function (RBF) is used to define the non-linear weight of the partial linear network. …”
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

“…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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Combining autoregressive integrated moving average with Long Short-Term Memory neural network and optimisation algorithms for predicting ground water level by Sheikh Khozani Z., Barzegari Banadkooki F., Ehteram M., Najah Ahmed A., El-Shafie A.

“…Brain; Forecasting; Genetic algorithms; Groundwater resources; Light modulators; Long short-term memory; Soil conservation; Time series; Water conservation; Water levels; Water management; Auto regressive integrated moving average models; Auto-regressive integrated moving average model model; Ground water level; Long short-term memory model; Memory modeling; Non linear; Optimisations; Optimization algorithms; Salp swarms; Times series; Groundwater…”

Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

“…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

“…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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