Search Results - (( _ implementation function algorithm ) OR ( using vectorization based algorithm ))

Smoothed functional algorithm with norm-limited update vector for identification of continuous-time fractional-order Hammerstein Models by Mok, Ren Hao, Mohd Ashraf, Ahmad

“…In particular, the standard smoothed functional algorithm (SFA) based method is modified by implementing a limit function in the update vector of the standard SFA based method to solve the issue of high tendency of divergence during the identification process. …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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MBIST implementation and evaluation in FPGA based on low-complexity March algorithms by Jidin, Aiman Zakwan, Mispan, Mohd Syafiq, Hussin, Razaidi, Weng, Fook Lee

“…This paper presents the implementation and validation of MBIST controllers that applied the March AZ1 and March AZ2 algorithms in a Field-Programmable Gate Array (FPGA) device. …”
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Transmission lines modeling based on vector fitting algorithm and RLC active/passive filter design by Turki, Ahmed Qasim, Mailah, Nashiren Farzilah, Othman, Mohammad Lutfi, Sabry, Ahmad H.

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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island by Mohd Shafri, Helmi Zulhaidi, Ramle, F. S. H.

“…The classification using SVM method was implemented automatically by using four kernel types; linear, polynomial, radial basis function and sigmoid. …”
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A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

“…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (ant) survival behavior, depict the common characteristics of both algorithms. Solution vector of ACO is presented by implementing density and distribution function to search for a better solution and to specify a probability functions for every particle (ant). …”
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Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

“…In the first scheme, a vectorized algorithm and automatic differentiation are implemented to minimize computational costs. …”
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Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

“…In this thesis, a new quaternion gradient based adaptive algorithm for FIR adaptive filter is developed. …”
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An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Design and implementation of a single-phase to three-phase space-vector pwm-based matrix converter system for induction motor drives by Velu, Vengadeshwaran

“…Digital Signal Processor is used as a control system to produce the switching sequences of the individual bidirectional switches based on space vector Pulse Width Modulation algorithm. …”
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Transmission lines modelling based on RLC passive and active filter design by Turki, Ahmed Qasim, Mailah, Nashiren Farzilah, Sabry, Ahmad H.

“…This paper presents a transmission line (TL) modelling which is based upon vector fitting algorithm and RLC passive filter design. …”
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A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Smart fall detection by enhanced SVM with fuzzy logic membership function by Harum, Norharyati, Khalil, Mohamad Kchouri, Hazimeh, Hussein, Obeid, Ali

“…In addition, they use thresholds to identify falls based on artificial experiences or machine learning (ML) algorithms. …”
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Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mahabob, Noratikah Zawani, Ismail, Nurlaila, Mohd Yusoff, Zakiah, Taib, Mohd Nasir

“…Support vector machine (SVM) has been chosen as a main model and for the specific function algorithm was multiclass function. …”
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Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques by Mustafa, Ahmed Sudad

“…Ad hoc on-demand distance vector routing protocol (AODV) is a commonly used protocol in MANET. …”
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam by Sarmad Dashti Latif, Mr.

“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”

A new technique for maximum load margin estimation and prediction by Aziz N.F.A., Rahman T.K.A., Yasin Z.M., Zakaria Z.

“…In addition, FAISVM is another new hybrid technique developed for maximum load margin prediction that integrates the application of FAIS and Support Vector Machine (SVM). For validation, FAISVM was compared with Evolutionary Support Vector Machine (ESVM) that uses Evolutionary Programming (EP) as the search algorithm. …”

SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration by Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A.

“…Data-driven models for predicting fire and explosion-related properties have been improved greatly in recent years using machine-learning algorithms. However, choosing the best machine learning approach is still a challenging task. …”
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Implementation of Symmetric Rank-One Methods for Unconstrained Optimization by Khiyaban, Farzin Modarres

“…The rate of convergence of such algorithms are also discussed. Due to the presence of SR1 deciencies, we introduce a restarting procedure using eigenvalue of the SR1 update. …”
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