Truncation error bounds for branched continued fraction whose partial denominators are equal to unity by R. I. Dmytryshyn, T. M. Antonova

“…The paper deals with the problem of obtaining error bounds for branched continued fraction of the form $\sum_{i_1=1}^N\frac{a_{i(1)}}{1}{\atop+}\sum_{i_2=1}^{i_1}\frac{a_{i(2)}}{1}{\atop+}\sum_{i_3=1}^{i_2}\frac{a_{i(3)}}{1}{\atop+}\ldots$. …”
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Controlling AoA Estimation Errors in Rician Fading via Measurement Quality Classification by Pedro Lemos, Glauber Brante, Ohara Kerusauskas Rayel, Richard Demo Souza

“…Angle of Arrival (AoA) estimation plays a crucial role in modern positioning systems but is often affected by errors in multipath channels. Existing methods typically lack a direct mechanism to assess the quality of the estimates, while full channel estimation using channel sounders is computationally expensive and impractical for many applications. …”
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Mutual coupling error modeling and correction of shared aperture interleaved sparse array antennas by Junming ZHUANG, Longjun LI

“…The shared aperture interleaved sparse array antenna is an effective way to implement a multi-function array antenna.The existing parameterized mutual coupling elimination methods are all developed for uniform array antennas.The mutual coupling matrix which is studied is a regular square matrix and is not applicable to the mutual coupling matrix model of the shared aperture interleaved sparse array antenna.After fully considering the speciality of “sparse” and “azimuth dependence” of mutual coupling in sub-arrays of a shared aperture interleaved sparse array antenna,the conventional mutual coupling matrix extension was expressed as “non-square” “enhanced mutual coupling matrix”.Coupling effects between subarrays and subarrays in interleaved arrays of sparse arrays were modeled,and the modeling and correction of mutual coupling errors in shared aperture sparse array antennas were finally achieved through the parameterization of “enhanced mutual coupling matrix”.Simulation results verify the effectiveness and feasibility of the proposed method.…”
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ESTIMATING TURKISH STOCK MARKET RETURNS WITH APT MODEL: COINTEGRATION AND VECTOR ERROR CORRECTION by Özge SEZGİN ALP, Fazıl GÖKGÖZ, Güray KÜÇÜKKOCAOĞLU

“…The relationship between main stock indices and macroeconomic variables has been submitted to cointegration tests and vector error correction model analyses. The results have revealed that significant macroeconomic variables vary upon sectors and have a long-run effect in determining stock indices. …”
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Symmetric Clifford twirling for cost-optimal quantum error mitigation in early FTQC regime by Kento Tsubouchi, Yosuke Mitsuhashi, Kunal Sharma, Nobuyuki Yoshioka

“…Abstract Twirling noise affecting quantum gates is essential in understanding and controlling errors, but applicable operations to noise are usually restricted by symmetries inherent in quantum gates. …”
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ESTIMATING TURKISH STOCK MARKET RETURNS WITH APT MODEL: COINTEGRATION AND VECTOR ERROR CORRECTION by Özge SEZGİN ALP, Fazıl GÖKGÖZ, Güray KÜÇÜKKOCAOĞLU

“…The relationship between main stock indices and macroeconomic variables has been submitted to cointegration tests and vector error correction model analyses. The results have revealed that significant macroeconomic variables vary upon sectors and have a long-run effect in determining stock indices. …”
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The Design Method of Enhanced Unscented Kalman Filter Considering UT Transform Truncation Error by Ziran Luo, Chenglin Wen

“…This inherent limitation introduces non negligible truncation errors into state estimation, leading to significantly degraded accuracy in practical applications such as high-maneuvering target tracking, robotic localization in complex environments, and high-precision inertial navigation. …”
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Research on Three-Dimensional Magnetic Induced Error Model of Interferometric Fiber Optic Gyro by Zicheng Wang, Guochen Wang, Wei Gao, Zhuo Wang

“…To improve the performance of IFOG, the accurate model of Faraday effect-induced bias errors is necessary for its practical applications. …”
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Generalized number-phase lattice encoding of a bosonic mode for quantum error correction by Dong-Long Hu, Weizhou Cai, Chang-Ling Zou, Ze-Liang Xiang

“…Abstract Bosonic systems offer unique advantages for quantum error correction, as a single bosonic mode provides a large Hilbert space to redundantly encode quantum information. …”
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Multiview Deep Autoencoder-Inspired Layerwise Error-Correcting Non-Negative Matrix Factorization by Yuan Liu, Yuan Wan, Zaili Yang, Huanhuan Li

“…To address these limitations, this study aims to develop a novel method that integrates an autoencoder-inspired structure into the deep NMF framework, incorporating layerwise error-correcting constraints. This approach can facilitate the extraction of hierarchical features while effectively mitigating reconstruction error accumulation in deep architectures. …”
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Model Predictive Control for Six-Phase Induction Machines with Insight into Past Current Errors by Juan Carrillo-Ríos, Ignacio González-Prieto, Ángel González-Prieto, Mario J. Durán, Juan José Aciego

“…Multi-phase electric drives can act as a competitive solution for high-power applications. To take advantage of the multi-phase benefits, the design of high-performance control techniques is a crucial task. …”
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Two-Step Single Slope/SAR ADC with Error Correction for CMOS Image Sensor by Fang Tang, Amine Bermak, Abbes Amira, Mohieddine Amor Benammar, Debiao He, Xiaojin Zhao

“…With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. …”
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Error Distribution Pattern Analysis of Mobile Laser Scanners for Precise As-Built BIM Generation by Sung-Jae Bae, Junbeom Park, Joonhee Ham, Minji Song, Jung-Yeol Kim

“…In other words, the results indicate that when using MLS for as-built BIM generation, robust fitting methods have limitations in obtaining realistic object dimensions, as they do not account for the unique error patterns present in MLS point clouds. The proposed method provides a simple and repeatable approach for enhancing MLS accuracy, contributing to improved dimensional reliability in MLS-driven BIM applications.…”
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Minimizing the Error Gap in Smart Framing by Forecasting Production and Demand Using ARIMA Model by Surindar Gopalrao Wawale, Malik Jawarneh, P. Naveen Kumar, Thomas Felix, Jyoti Bhola, Roop Raj, Sathyapriya Eswaran, Rajasekhar Boddu

“…To develop grain price estimates, researchers used Autoregressive Integrated Moving Average (ARIMA) methods, and the precision of the forecasts was examined using conventional mean square error (MSE) and mean absolute percentage error (MAPE) standards. …”
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Brain computer interface based emotion recognition with error analysis and challenges: an interdisciplinary review by Niharika Gudikandula, Ravichander Janapati, Rakesh Sengupta, Sridhar Chintala

“…Therefore, emotion recognition through BCIs holds significant promise for various domains, including affective computing, healthcare, and human–computer interaction, with numerous potential applications. Creating precise and reliable emotion recognition systems based on BCIs presents significant challenges due to the multitude of potential error sources that can affect their effectiveness. …”
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Mobile Location With Multi-Spot Measurements Model Considering Anchor Node Position Errors by Chenyu Yang, Rui Ren, Dongkun Jin, Jiyan Huang

“…However, practical implementation of multi-spot techniques faces challenges when anchor nodes are subject to motion and position errors, which can substantially impact the accuracy of position estimation. …”
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Evaluation of the soft error assessment consistency of a JIT‐based virtual platform simulator by Geancarlo Abich, Rafael Garibotti, Vitor Bandeira, Felipe da Rosa, Jonas Gava, Felipe Bortolon, Guilherme Medeiros, Fernando G. Moraes, Ricardo Reis, Luciano Ost

“…Campaigns consider different open‐source and commercial compilers as well as real software stacks including FreeRTOS/Linux kernels and 52 applications. Results show that OVPsim‐FIM is more than 1000× faster than cycle‐accurate simulators and up to 312× faster than event‐driven simulators, while preserving the soft error analysis accuracy (i.e. mismatch below to 10%) for single and multicore processors.…”
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A Comprehensive Review of Mathematical Error Characterization and Mitigation Strategies in Terrestrial Laser Scanning by Mansoor Sabzali, Lloyd Pilgrim

“…This research focused on investigating four primary sources of error in the generic error model of TLS. These were categorized into four geometries: instrumental imperfections related to the scanner itself, atmospheric effects that impact the laser beam, scanning geometry concerning the setup and varying incidence angles during scanning, and object and surface characteristics affecting the overall data accuracy. …”
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Modeling Time Series with SARIMAX and Skew-Normal and Zero-Inflated Skew-Normal Errors by M. Alejandro Dinamarca, Fernando Rojas, Claudia Ibacache-Quiroga, Karoll González-Pizarro

“…This study proposes an extension of Seasonal Autoregressive Integrated Moving Average models with exogenous regressors (SARIMAX) by incorporating skew-normal and zero-inflated skew-normal error structures to better accommodate asymmetry and excess zeros in time series data. …”
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Robust prediction of chaotic systems with random errors using dynamical system deep learning by Zixiang Wu, Jianping Li, Hao Li, Mingyu Wang, Ning Wang, Guangcan Liu

“…Our work extends the theoretical applicability of the DSDL under random error conditions and points to the new and superior data-driven method DSDL based on the dynamic framework, holding significant potential for mitigating the impact of random errors and achieving robust predictions of real-world systems.…”
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