Article
Engineering, Electrical & Electronic
Daniel Belega, Dario Petri
Summary: This article analyzes the impact of frequency error on amplitude and phase estimation, deriving a constraint to ensure accuracy of the estimates. By deriving expressions for MSE under the assumption of small frequency error, the study investigates the influence of frequency uncertainty on the algorithm.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Mathematics, Applied
Feng Ding
Summary: Least squares is an important method used for solving linear fitting and quadratic optimization problems. This paper explores the properties of least squares methods and multi-innovation least squares methods, and demonstrates important contributions in the area of system identification such as auxiliary model identification, multi-innovation identification theory, hierarchical identification principle, coupling identification concept, and filtering identification idea. The results of least squares and multi-innovation least squares algorithms for linear regressive systems with white noises can be extended to systems with colored noises.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2023)
Article
Chemistry, Multidisciplinary
Yung-An Kao, Kun-Feng Wu
Summary: This paper proposes a low-complexity least-squares (LS) method to solve the leakage effect problem in DFT-based channel estimation. Compared to other methods, this method does not require knowledge of the statistical properties of the channel or the insertion of extra pilots, and has similar channel estimation efficiency to the LS method in simulation.
APPLIED SCIENCES-BASEL
(2022)
Article
Optics
Yong -Mei Li, Hai -Ling Liu, Shi-Jie Pan, Su-Juan Qin, Fei Gao, Dong-Xu Sun, Qiao-Yan Wen
Summary: This paper proposes a complete quantum algorithm for the k-medoids algorithm, which utilizes quantum subroutines to improve the speed of cluster assignment and center update. Compared to existing algorithms, our quantum k-medoids algorithm achieves a polynomial speedup in large data sets.
Article
Engineering, Mechanical
Rohit Rana, Prerna Gaur, Vijyant Agarwal, Harish Parthasarathy
Summary: The research focuses on accurately estimating parameters from compressed temporal data in the presence of noise. The proposed method utilizes the properties of recursive wavelet domain to selectively store noise-free data coefficients, achieving data compression. The algorithm can be implemented on any scalable VLSI circuit and has been experimentally demonstrated on the Omni Bundle robot.
NONLINEAR DYNAMICS
(2022)
Review
Engineering, Mechanical
Randall J. Allemang, Rohit S. Patwardhan, Murali M. Kolluri, Allyn W. Phillips
Summary: This paper outlines various FRF estimation techniques and compares algorithms that compute FRF using different methods. It also discusses inconsistencies in some conditioned coherence metrics and provides corrected interpretations.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Automation & Control Systems
Yelong Yu, Xiaoyan Huang, Zhaokai Li, Min Wu, Tingna Shi, Yanfei Cao, Geng Yang, Feng Niu
Summary: This article introduces a novel online full parameter estimation method for permanent magnet synchronous motors (PMSMs). By utilizing the recursive least squares algorithm in the alpha-beta frame, the proposed method can estimate all motor parameters simultaneously. Simulation and experimental results demonstrate the superiority of the proposed method in terms of convergence rate, computational cost, and accuracy compared to the traditional method in the d-q frame.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Mathematics
Yan Ji, Jinde Cao
Summary: This paper addresses the parameter estimation problems of Hammerstein FIR-MA systems. Two models are constructed based on matrix transformation and hierarchical identification principle, and recursive least-squares algorithm and multi-innovation hierarchical least-squares algorithm are proposed for parameter estimation. The effectiveness of the proposed algorithms is demonstrated through a simulation example.
Article
Engineering, Electrical & Electronic
Zhe Li
Summary: This paper proposes a robust technique for fundamental frequency estimation in unbalanced three-phase power systems, which enhances immunity to noise and harmonic pollution by minimizing error vectors. Simulations demonstrate the performance advantage of this algorithm over other smart discrete Fourier transform based methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Multidisciplinary Sciences
Esref Bogar
Summary: This paper proposes a novel hybrid algorithm called CGO-LS for accurately estimating the parameters of photovoltaic models. By adopting a cascade estimation strategy based on parameter decomposition, CGO-LS combines the nonlinear optimization capability of CGO and the power of the LS estimator. Experimental results demonstrate that CGO-LS possesses superior estimation performance and excellent robustness in emulating experimental datasets.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Mathematics, Interdisciplinary Applications
Chaeyoung Lee, Soobin Kwak, Sangkwon Kim, Youngjin Hwang, Yongho Choi, Junseok Kim
Summary: This study introduces a robust optimal parameter estimation method for the SUC epidemic dynamics model, which fixes one parameter and optimizes the others to best fit the confirmed population. Numerical experiments with synthetic and real-world data support the robustness and practical application of the proposed method.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Multidisciplinary
Baolei Wei
Summary: Parameter estimation is a crucial step in grey system models for time series modeling and forecasting. This study presents a separable grey system model that encompasses both linear and nonlinear models with separable structural parameters. Three least squares-based strategies are proposed for estimating structural parameters and initial conditions. Nonlinear least squares outperforms the other two strategies, especially in scenarios with large time intervals and high noise levels. Real-world applications demonstrate the effectiveness of the proposed method in forecasting failure times of products and traffic flows.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Instruments & Instrumentation
Liwei Ni, Wenze Qiu, Jialei Jin, Qiyue Xu, Shuliang Ye
Summary: An algorithm based on reaction kinetic modeling and partial least squares (PLS) chemometric method is proposed for comprehensive and quantitative study of chemical reaction processes. The algorithm allows simultaneous calculation of concentration profiles and apparent kinetic parameters from spectral data, without the need for complicated analysis or sampling efforts. The method has been validated with Paal-Knorr reactions and glyoxylic acid synthesis reactions, showing good accuracy and potential for process optimization.
APPLIED SPECTROSCOPY
(2022)
Article
Energy & Fuels
Oumaima Mesbahi, Mouhaydine Tlemcani, Fernando M. Janeiro, Abdeloawahed Hajjaji, Khalid Kandoussi
Summary: This study presents a new cost function based on Total Least Squares for photovoltaic parameter extraction and compares its performance with the traditional Ordinary Least Squares approach. The performance of the two cost functions is evaluated using eleven different optimization methods for both single and double diode photovoltaic cell models. The results show that the Total Least Squares method performs better in parameter estimation and achieves the best results when coupled with Teaching Learning Based Optimization algorithm. The convergence properties of the two cost functions are also compared, showing a significant difference with the Dragonfly method.
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
(2022)
Article
Acoustics
Nezih Topaloglu, Cevat V. Karadag
Summary: A linear regression based SDOF resonator parameter extraction method is proposed, which outperforms other methods using amplitude FRF.
JOURNAL OF SOUND AND VIBRATION
(2022)