Search Results - (( square estimation path algorithm ) OR ( based optimization based algorithm ))
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1
Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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2
Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture
Published 2010“…The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. …”
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3
All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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4
Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…Filtered-X least mean square (FXLMS) control algorithm is a conventional algorithm employed to cancel the noise in linear environment. …”
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Associated Factors of Cardiovascular Diseases in Pakistan: Assessment of Path Analyses Using Warp Partial Least Squares Estimation
Published 2020“…The information on demographic, SE, modifiable and clinical factors of CVDs was recorded. Warp partial least squares (PLS) based on warp 3 algorithm was used to estimate the simultaneous linear and non-linear path coefficients of the proposed model of study. …”
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6
Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…The warppartial least square method was utilized to estimate the multi-layer hypothesized path model. …”
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7
Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity
Published 2014“…The proposed THF-NLFXLMS algorithm models the Wiener secondary path and applies the estimated degree of nonlinearity of the nonlinear secondary path in the control algorithm design. …”
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8
Development of the propagation paths and deriving observer of feedforward active noise control system by using state-space formulation
Published 2010“…Furthermore, a new observer namely State Space Least Mean Square (SSLMS) observer will be derived. This observer will be used to estimate the states along the propagation path which can not be estimated using LMS algorithm because LMS based on the FIR models. …”
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9
Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity
Published 2016“…The proposed THF-NLFXLMS algorithm, models the nonlinear secondary path and applies the estimated degree of nonlinearity in the control algorithm design. …”
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10
Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks
Published 2021“…To implement the ILMS algorithm, each node needs to receive the local estimate of the previous node on the cycle path to update its own local estimate. …”
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11
Identification and mitigation of non-line-of-sight path effect using repeater for hybrid ultra-wideband positioning and networking system
Published 2021“…In this paper, we propose a hybrid indoor UWB positioning and networking system that utilises the existing repeater of the data network to eliminate the NLOS paths. A switching algorithm is written to identify the existence of NLOS paths based on received signal strength (RSS) and unique channel characteristics such as mean excess delay (MED) and root mean square (RMS). …”
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12
Performance comparison of LFXLMS, MOVFXLMS and THF-NLFXLMS algorithms for Hammerstein NANC
Published 2016“…Filtered-X least mean square (FXLMS) algorithm is widely used in active noise control (ANC) systems when the secondary path is linear. …”
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13
Opposition-based Whale Optimization Algorithm
Published 2018“…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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14
Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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15
Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Published 2015“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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16
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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17
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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18
Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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19
Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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