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Journal articles on the topic 'Non-linear fusion'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Zhang, Jialiang, Jianfu Cao, and Feng Gao. "Fault diagnosis for multivariable non-linear systems based on non-linear spectrum feature." Transactions of the Institute of Measurement and Control 39, no. 7 (2016): 1017–26. http://dx.doi.org/10.1177/0142331215625766.

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In this study, a novel fault diagnosis approach based on a non-linear spectrum feature is proposed for a multivariable non-linear system. The non-linear spectrum features are obtained using a non-linear output frequency response function (NOFRF) and kernel principal component analysis (KPCA). In order to improve the real-time performance of obtaining non-linear spectrum features, a frequency domain variable step size normalized least mean square (FVLMS) adaptive algorithm is presented to identify NOFRF. A multi-fault classifier based on the fusion of a support vector machine (SVM) is designed

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2

Gong, Zhi Hua, Peng Wei Duan, Yong Guang Li, and Rui Yue. "Multi-Structural Non-Linear Data Fusion Method." Applied Mechanics and Materials 530-531 (February 2014): 554–60. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.554.

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In systematic measurement and control mode composed of optics, radar and telemetry, trajectory measurement is in need of high precision. So, based on exterior trajectory parameter expressed by Hermite function, this paper proposes a multi-structure data fusion method with multisource heterogeneous measuring elements, which is called function restraint EMBET method. Based on the fusion simulation calculation and analysis of the same data of multisource heterogeneous measuring elements both using general EMBET method and function restraint EMBET method, it is proved that function restraint EMBET

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3

Parisotto, Simone, Luca Calatroni, Aurelie Bugeau, Nicolas Papadakis, and Carola-Bibiane Schonlieb. "Variational Osmosis for Non-Linear Image Fusion." IEEE Transactions on Image Processing 29 (2020): 5507–16. http://dx.doi.org/10.1109/tip.2020.2983537.

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Fang, Aiqing, Xinbo Zhao, Jiaqi Yang, Yanning Zhang, and Xiang Zheng. "Non-linear and selective fusion of cross-modal images." Pattern Recognition 119 (November 2021): 108042. http://dx.doi.org/10.1016/j.patcog.2021.108042.

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Azmani, Monir, Serge Reboul, and Mohammed Benjelloun. "Non-Linear Fusion of Observations Provided by Two Sensors." Entropy 15, no. 12 (2013): 2698–715. http://dx.doi.org/10.3390/e15072698.

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6

Fiore, R., P. V. Sasorov, and V. R. Zoller. "Non-linear BFKL dynamics: Color screening vs. gluon fusion." JETP Letters 96, no. 11 (2013): 687–93. http://dx.doi.org/10.1134/s0021364012230063.

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González-Cruz, Darío. "Optimal Integration of Data Fusion in Solar Power Analytics: Enhancing Efficiency and Accuracy." Fusion: Practice and Applications 14, no. 2 (2024): 211–18. http://dx.doi.org/10.54216/fpa.140217.

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At the forefront of sustainable energy solutions lies renewable energy, particularly solar power. Nevertheless, the optimization of solar power systems necessitates comprehensive analytics, especially for proactive maintenance fault anticipation. This research evaluates data fusion techniques using both linear and non-linear regression models for predicting faults in solar power plants. The study begins with careful data preparation processes to ensure clean and harmonized data sets that include irradiation, temperature, historical fault records, and yield. Linear regression techniques provide

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Helps, O. R., A. L. Clarke, P. I. Nicholson, T. L. Burnett, and P. J. Withers. "Non-linear fusion of dual-energy projections for XCT imaging of challenging components." Proceedings of the Annual British Conference on Non-Destructive Testing 2023, no. 1 (2023): 1–12. http://dx.doi.org/10.1784/ndt2023.2c5.

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The imaging of multi-material components having large changes in attenuation behaviour is widely regarded as a limitation of X-ray computed tomographic techniques. The use of Dual Energy X-ray Computed Tomography (DECT) is common in the field of medical imaging, providing many benefits to imaging and characterisation. However, multienergy methods such as DECT remain underutilised in the industrial sector. In this work, a novel measurement based multi-energy image fusion approach was evaluated using two radiographic image stacks acquired under two distinct polychromatic spectra; this fusion was

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GE, Quan-Bo, Wen-Bin LI, Ruo-Yu SUN, and Zi XU. "Centralized Fusion Algorithms Based on EKF for Multisensor Non-linear Systems." Acta Automatica Sinica 39, no. 6 (2014): 816–25. http://dx.doi.org/10.3724/sp.j.1004.2013.00816.

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10

Sanroma, Gerard, Oualid M. Benkarim, Gemma Piella, et al. "Learning non-linear patch embeddings with neural networks for label fusion." Medical Image Analysis 44 (February 2018): 143–55. http://dx.doi.org/10.1016/j.media.2017.11.013.

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11

Zocco, A., P. Helander, and H. Weitzner. "Magnetic reconnection in 3D fusion devices: non-linear reduced equations and linear current-driven instabilities." Plasma Physics and Controlled Fusion 63, no. 2 (2020): 025001. http://dx.doi.org/10.1088/1361-6587/abcab3.

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12

Patel, B. S., D. Dickinson, C. M. Roach та H. R. Wilson. "Linear gyrokinetic stability of a high β non-inductive spherical tokamak". Nuclear Fusion 62, № 1 (2021): 016009. http://dx.doi.org/10.1088/1741-4326/ac359c.

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Abstract Spherical tokamaks (STs) have been shown to possess properties desirable for a fusion power plant such as achieving high plasma β and having increased vertical stability. To understand the confinement properties that might be expected in the conceptual design for a high β ST fusion reactor, a 1 GW ST plasma equilibrium was analysed using local linear gyrokinetics to determine the type of micro-instabilities that arise. Kinetic ballooning modes and micro-tearing modes are found to be the dominant instabilities. The parametric dependence of these linear modes was determined and, from th

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13

Li, Zi Yu, Yan Liu, Ping Zhu, and Cheng Ying. "Federated Particle Filter Technology Based on JIDS/SINS/GPS Integrated Navigation System." Applied Mechanics and Materials 347-350 (August 2013): 1544–48. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1544.

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In multi-sensor integrated navigation systems, when sub-systems are non-linear and with Gaussian noise, the federated Kalman filter commonly used generates large error or even failure when estimating the global fusion state. This paper, taking JIDS/SINS/GPS integrated navigation system as example, proposes a federated particle filter technology to solve problems above. This technology, combining the particle filter with the federated Kalman filter, can be applied to non-linear non-Gaussian integrated system. It is proved effective in information fusion algorithm by simulated application, where

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Zheng, Yuhui, Huihui Song, Le Sun, Zebin Wu, and Byeungwoo Jeon. "Spatiotemporal Fusion of Satellite Images via Very Deep Convolutional Networks." Remote Sensing 11, no. 22 (2019): 2701. http://dx.doi.org/10.3390/rs11222701.

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Spatiotemporal fusion provides an effective way to fuse two types of remote sensing data featured by complementary spatial and temporal properties (typical representatives are Landsat and MODIS images) to generate fused data with both high spatial and temporal resolutions. This paper presents a very deep convolutional neural network (VDCN) based spatiotemporal fusion approach to effectively handle massive remote sensing data in practical applications. Compared with existing shallow learning methods, especially for the sparse representation based ones, the proposed VDCN-based model has the foll

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Wu, Buchen, and Jiwei Qin. "A List-Ranking Framework Based on Linear and Non-Linear Fusion for Recommendation from Implicit Feedback." Entropy 24, no. 6 (2022): 778. http://dx.doi.org/10.3390/e24060778.

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Although most list-ranking frameworks are based on multilayer perceptrons (MLP), they still face limitations within the method itself in the field of recommender systems in two respects: (1) MLP suffer from overfitting when dealing with sparse vectors. At the same time, the model itself tends to learn in-depth features of user–item interaction behavior but ignores some low-rank and shallow information present in the matrix. (2) Existing ranking methods cannot effectively deal with the problem of ranking between items with the same rating value and the problem of inconsistent independence in re

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Di Maio, P. A., R. Giammusso, and G. Vella. "On the hyperporous non-linear elasticity model for fusion-relevant pebble beds." Fusion Engineering and Design 85, no. 7-9 (2010): 1234–44. http://dx.doi.org/10.1016/j.fusengdes.2010.03.015.

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Montes, H., L. Pedraza, M. Armada, T. Akinfiev, and R. Caballero. "Adding extra sensitivity to the SMART non‐linear actuator using sensor fusion." Industrial Robot: An International Journal 31, no. 2 (2004): 179–88. http://dx.doi.org/10.1108/01439910410522856.

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Perrin, M. C., D. E. Ruester, and B. A. Cramer. "A Computer Code to Calculate Non-Linear Stresses in a Fusion Reactor." Fusion Technology 8, no. 1P2A (1985): 592–95. http://dx.doi.org/10.13182/fst85-a40103.

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Anzalone, Andrea, Federico Bizzarri, Marco Storace, and Mauro Parodi. "A cellular non-linear network for image fusion based on data regularization." International Journal of Circuit Theory and Applications 34, no. 5 (2006): 533–46. http://dx.doi.org/10.1002/cta.354.

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SEO, Kouki, Chihiro GO, Yuma KINOSHITA, and Hitoshi KIYA. "Hue-Correction Scheme Considering Non-Linear Camera Response for Multi-Exposure Image Fusion." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E103.A, no. 12 (2020): 1562–70. http://dx.doi.org/10.1587/transfun.2020smp0026.

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21

Lu, Kelin, Changyin Sun, Qien Fu, and Qian Zhu. "Distributed track‐to‐track fusion for non‐linear systems with Gaussian mixture noise." IET Radar, Sonar & Navigation 13, no. 5 (2019): 740–49. http://dx.doi.org/10.1049/iet-rsn.2018.5186.

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22

Abuturab, Muhammad Rafiq. "Gyrator wavelet transform based non-linear multiple single channel information fusion and authentication." Optics Communications 355 (November 2015): 462–78. http://dx.doi.org/10.1016/j.optcom.2015.06.069.

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23

Frerichs, H., and D. Reiter. "Stability and control of iterated non-linear transport solvers for fusion edge plasmas." Computer Physics Communications 188 (March 2015): 82–87. http://dx.doi.org/10.1016/j.cpc.2014.11.007.

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24

Mensah, David Kwamena, Micheal Arthur Ofori, George Otieno Orwa, and Paul Hewson. "Traumatic Physiological Vital Sign Fusion: Insight from Composite Spatial Similarity Measure Modelling." Journal of Multidisciplinary Applied Natural Science 5, no. 2 (2025): 698–712. https://doi.org/10.47352/jmans.2774-3047.275.

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This paper develops a non-linear composite similarity-based framework for generating univariate physiological vital signs data from an input multivariate counterpart. The framework is built on mixture random variate using information provided by the inter-relationships among variables. This allows the latent one-dimensional data to be generated as a weighted linear combination of the multivariate data, providing an easy way to model the weights in terms of desirable data features of interest. Using variable specific non-linear composite similarity statistic to handle short, medium- and long-te

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Keneskyzy, K., та S. B. Yeskermes. "Метод машинного обучения для обратных задач теплопроводности". INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES 2, № 1(5) (2021): 59–64. http://dx.doi.org/10.54309/ijict.2021.05.1.008.

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Investigated in this work is the potential of carrying out inverse problems with linear and non-linear behavior using machine learning methods and the neural network method. With the advent of ma-chine learning algorithms it is now possible to model inverse problems faster and more accurately. In order to demonstrate the use of machine learning and neural networks in solving inverse problems, we propose a fusion between computational mechanics and machine learning. The forward problems are solved first to create a database. This database is then used to train the machine learning and neural ne

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26

Gajjar, Bhavinkumar, Hiren Mewada, and Ashwin Patani. "Sparse coded spatial pyramid matching and multi-kernel integrated SVM for non-linear scene classification." Journal of Electrical Engineering 72, no. 6 (2021): 374–80. http://dx.doi.org/10.2478/jee-2021-0053.

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Abstract Support vector machine (SVM) techniques and deep learning have been prevalent in object classification for many years. However, deep learning is computation-intensive and can require a long training time. SVM is significantly faster than Convolution Neural Network (CNN). However, the SVM has limited its applications in the mid-size dataset as it requires proper tuning. Recently the parameterization of multiple kernels has shown greater flexibility in the characterization of the dataset. Therefore, this paper proposes a sparse coded multi-scale approach to reduce training complexity an

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27

Blyth, Sue, and Gillian Straker. "Intimacy, Fusion and Frequency of Sexual Contact in Lesbian Couples." South African Journal of Psychology 26, no. 4 (1996): 253–56. http://dx.doi.org/10.1177/008124639602600409.

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It is generally accepted in the literature that, of all couple types, lesbian couples tend to have the lowest frequencies of sexual contact. It has been hypothesized that a reason for this is that lesbian couples are more subject than others to fusion. This study examines the relationship between frequency of sexual contact and fusion in lesbian relationships of duration longer than one year. The concept of fusion has, however, not been clearly defined. Although Mencher (1990), for example, states that fusion is akin to, but not the same as, intense intimacy, fusion is treated within the liter

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Seo, Dae Kyo, and Yang Dam Eo. "A Learning-Based Image Fusion for High-Resolution SAR and Panchromatic Imagery." Applied Sciences 10, no. 9 (2020): 3298. http://dx.doi.org/10.3390/app10093298.

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Image fusion is an effective complementary method to obtain information from multi-source data. In particular, the fusion of synthetic aperture radar (SAR) and panchromatic images contributes to the better visual perception of objects and compensates for spatial information. However, conventional fusion methods fail to address the differences in imaging mechanism and, therefore, they cannot fully consider all information. Thus, this paper proposes a novel fusion method that both considers the differences in imaging mechanisms and sufficiently provides spatial information. The proposed method i

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Zhang, Anqing, Wanshun Zhang, and Haiming Qi. "The Non-linear Tracking of IMM- PHD Filter for Rader-Infrared Sensor Data Fusion." Journal of Physics: Conference Series 1624 (October 2020): 032038. http://dx.doi.org/10.1088/1742-6596/1624/3/032038.

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Wang, Meng, Changzhi Luo, Bingbing Ni, Jun Yuan, Jianfeng Wang, and Shuicheng Yan. "First-Person Daily Activity Recognition With Manipulated Object Proposals and Non-Linear Feature Fusion." IEEE Transactions on Circuits and Systems for Video Technology 28, no. 10 (2018): 2946–55. http://dx.doi.org/10.1109/tcsvt.2017.2716819.

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Gialampoukidis, Ilias, Anastasia Moumtzidou, Dimitris Liparas, Theodora Tsikrika, Stefanos Vrochidis, and Ioannis Kompatsiaris. "Multimedia retrieval based on non-linear graph-based fusion and partial least squares regression." Multimedia Tools and Applications 76, no. 21 (2017): 22383–403. http://dx.doi.org/10.1007/s11042-017-4797-4.

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Cooke, S. R., C. W. Sinclair, and D. M. Maijer. "Incorporating non-linear effects in fast semi-analytical thermal modelling of powder bed fusion." Additive Manufacturing 84 (March 2024): 104139. http://dx.doi.org/10.1016/j.addma.2024.104139.

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Asthana, Tanmay, Hamid Krim, Xia Sun, Siddharth Roheda, and Lian Xie. "Atlantic Hurricane Activity Prediction: A Machine Learning Approach." Atmosphere 12, no. 4 (2021): 455. http://dx.doi.org/10.3390/atmos12040455.

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Long-term hurricane predictions have been of acute interest in order to protect the community from the loss of lives, and environmental damage. Such predictions help by providing an early warning guidance for any proper precaution and planning. In this paper, we present a machine learning model capable of making good preseason-prediction of Atlantic hurricane activity. The development of this model entails a judicious and non-linear fusion of various data modalities such as sea-level pressure (SLP), sea surface temperature (SST), and wind. A Convolutional Neural Network (CNN) was utilized as a

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Yuan, Zhengwu, Qiang Chen, Wen Shao, and Zhiwei Yang. "Remote sensing image classification based on non-linear enhanced attention mechanism." Journal of Physics: Conference Series 2870, no. 1 (2024): 012002. http://dx.doi.org/10.1088/1742-6596/2870/1/012002.

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Abstract In recent years, Transformer technology has gradually shown promising applications in the field of computer vision, becoming a research hotspot. However, traditional vision Transformers suffer from significant computational burdens. Although previous studies have attempted to alleviate this issue by reducing the computational load of attention mechanisms, their methods still require improvement. Additionally, past research often overlooked the non-linear representation of values within attention mechanisms, posing another challenge to address. Therefore, this paper proposes a novel at

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Mafata, Mpho, Jeanne Brand, and Astrid Buica. "Data fusion using Multiple Factor Analysis coupled with non-linear pattern recognition (fuzzy k-means): application to Chenin blanc." OENO One 56, no. 3 (2022): 413–25. http://dx.doi.org/10.20870/oeno-one.2022.56.3.5374.

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Patterns in data obtained from wine chemical and sensory evaluations are difficult to decipher using classical statistics. Coupling data fusion with machine learning techniques could assist in solving these issues and lead to new hypotheses. The current study investigated the applicability of classical and machine learning pattern recognition approaches for oenological applications. A sample set of 23 Chenin blanc wines made from young (< 35 years) and old (> 35 years) vines were analysed (recently bottled (Year 1) and after two years of storage (Year 2)). Sensory (sorting) and chemical

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Turiel, A., J. Isern-Fontanet, and M. Umbert. "Sensibility to noise of new multifractal fusion methods for ocean variables." Nonlinear Processes in Geophysics 21, no. 1 (2014): 291–301. http://dx.doi.org/10.5194/npg-21-291-2014.

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Abstract. The repeated observation of the same signatures of mesoscale and submesoscale features in different ocean variables indicates that some common, non-linear processes affect them to a significant extent. A new method to exploit these common signatures to improve the quality of a noisy variable (i.e. increasing the signal-to-noise ratio) using another variable as template has recently been introduced. The method is based on superimposing the multifractal structure of singularity exponents from the template variable to the variable to be enhanced. In this paper, we will discuss the sensi

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Xu, Fu Yong, Ren Rong Liu, Ling Xu, Xue Mei Qiu, and Li Xin Zhu. "Two Expression Vectors, Designated as pGEX-CDON and pC89S4-CDON, for Producing GST-CDON and pVIII-CDON Fusion Proteins." Advanced Materials Research 726-731 (August 2013): 505–10. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.505.

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Deoxynivalenol (DON) mimotope, designated as CDON, is an epitope (CMRPWLQ) immunoscreened from a phage-displayed random peptide library. In order to replace the conjugated toxin with non-toxic recombinant proteins in ELISA, two novel expression vectors, which were designated as plasmid pGEX-CDON and phagemid pC89S4-CDON for producing GST-CDON and pVIII-CDON fusion proteins in E.coli were constructed. After purification, both GST-CDON and pVIII-CDON fusion proteins show good reactogenicity with an anti-DON antibody in a competitive inhibition ELISA test. When GST-CDON was used as coating antige

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Elmannai, H., M. A. Loghmari, and M. S. Naceur. "TWO LEVELS FUSION DECISION FOR MULTISPECTRAL IMAGE PATTERN RECOGNITION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-2/W2 (October 19, 2015): 69–74. http://dx.doi.org/10.5194/isprsannals-ii-2-w2-69-2015.

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Major goal of multispectral data analysis is land cover classification and related applications. The dimension drawback leads to a small ratio of the remote sensing training data compared to the number of features. Therefore robust methods should be associated to overcome the dimensionality curse. The presented work proposed a pattern recognition approach. Source separation, feature extraction and decisional fusion are the main stages to establish an automatic pattern recognizer. <br><br> The first stage is pre-processing and is based on non linear source separation. The mixing pro

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Deo, Ankur, and Vasile Palade. "Switching Trackers for Effective Sensor Fusion in Advanced Driver Assistance Systems." Electronics 11, no. 21 (2022): 3586. http://dx.doi.org/10.3390/electronics11213586.

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Modern cars utilise Advanced Driver Assistance Systems (ADAS) in several ways. In ADAS, the use of multiple sensors to gauge the environment surrounding the ego-vehicle offers numerous advantages, as fusing information from more than one sensor helps to provide highly reliable and error-free data. The fused data is typically then fed to a tracker algorithm, which helps to reduce noise and compensate for situations when received sensor data is temporarily absent or spurious, or to counter the offhand false positives and negatives. The performances of these constituent algorithms vary vastly und

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ZHANG, WEN-RAN. "YINYANG BIPOLAR LATTICES AND L-SETS FOR BIPOLAR KNOWLEDGE FUSION, VISUALIZATION, AND DECISION." International Journal of Information Technology & Decision Making 04, no. 04 (2005): 621–45. http://dx.doi.org/10.1142/s0219622005001763.

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YinYang bipolar sets, bipolar lattice, bipolar L-crisp sets, and Bipolar L-fuzzy sets are presented for bipolar information/knowledge fusion, visualization, and decision. First, a bipolar lattice B is defined as a 4-tuple (B, ⊕, &, ⊗) in which every pair of elements has a bipolar lub (blub ⊕), a bipolar glb (bglb &), and a cross-pole glb (cglb ⊗). A bipolar L-set (crisp or fuzzy) B = (B-, B+) in X to a bipolar lattice BL is defined as a bipolar equilibrium function or mapping B : X ⇒ BL. A strict bipolar lattice B is defined as a 7-tuple (B, ≡, ⊕, ⊗, &, -, ¬, ⇒) that delegates a cl

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BIN, LIU, and JIAXIONG PENG. "IMAGE FUSION METHOD BASED ON SHORT SUPPORT SYMMETRIC NON-SEPARABLE WAVELET." International Journal of Wavelets, Multiresolution and Information Processing 02, no. 01 (2004): 87–98. http://dx.doi.org/10.1142/s0219691304000330.

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In this paper, image fusion method based on a new class of wavelet — non-separable wavelet with compactly supported, linear phase, orthogonal and dilation matrix [Formula: see text] is presented. We first construct a non-separable wavelet filter bank. Using these filters, the images involved are decomposed into wavelet pyramids. Then the following fusion algorithm was proposed: for low-frequency part, the average value is selected for new pixel value, For the three high-frequency parts of each level, the standard deviation of each image patch over 3×3 window in the high-frequency sub-images is

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Lu, Jiyong, Weizhen Wang, Li Li, and Yanping Guo. "Distributed fusion estimation for non-linear networked systems with random access protocol and cyber attacks." IET Control Theory & Applications 14, no. 17 (2020): 2491–98. http://dx.doi.org/10.1049/iet-cta.2020.0040.

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Singh, Chandan, Ekta Walia, and Kanwal Preet Kaur. "Enhancing color image retrieval performance with feature fusion and non-linear support vector machine classifier." Optik 158 (April 2018): 127–41. http://dx.doi.org/10.1016/j.ijleo.2017.11.202.

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Singh, Narinder, Le Hoang Son, Francisco Chiclana, and Jean-Pierre Magnot. "A new fusion of salp swarm with sine cosine for optimization of non-linear functions." Engineering with Computers 36, no. 1 (2019): 185–212. http://dx.doi.org/10.1007/s00366-018-00696-8.

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Nigama Prasan Sahoo. "Investigating the Role of Nonlinearity in Plasma Wave Dynamics: Theoretical and Computational Perspectives." Advances in Nonlinear Variational Inequalities 28, no. 4s (2025): 366–79. https://doi.org/10.52783/anvi.v28.3338.

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Plasma waves are fundamental for understanding many plasma phenomena, and at high enough amplitudes, the wave can also become nonlinear and complex. Research on nonlinear dynamics of plasma waves is critical for many applications, including fusion energy, space physics and plasma engineering. Theoretical aspects of nonlinear plasma wave propagation: wave packets, solitons, modulation instability, and wave-particle interaction. We generalize the standard theories of plasma waves to include non-linear terms and discuss how these non-linear equations can be solved numerically. We further discuss

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Shen, Aojie, Yanchen Bo, Wenzhi Zhao, and Yusha Zhang. "Impact of the Dates of Input Image Pairs on Spatio-Temporal Fusion for Time Series with Different Temporal Variation Patterns." Remote Sensing 14, no. 10 (2022): 2431. http://dx.doi.org/10.3390/rs14102431.

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Dense time series of remote sensing images with high spatio-temporal resolution are critical for monitoring land surface dynamics in heterogeneous landscapes. Spatio-temporal fusion is an effective solution to obtaining such time series images. Many spatio-temporal fusion methods have been developed for producing high spatial resolution images at frequent intervals by blending fine spatial images and coarse spatial resolution images. Previous studies have revealed that the accuracy of fused images depends not only on the fusion algorithm, but also on the input image pairs being used. However,

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Yi, Changyu, Minzhe Li, and Shuyi Li. "Multi-Sensor Fusion Target Tracking Based on Maximum Mixture Correntropy in Non-Gaussian Noise Environments with Doppler Measurements." Information 14, no. 8 (2023): 461. http://dx.doi.org/10.3390/info14080461.

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This paper addresses the multi-sensor fusion target tracking problem based on maximum mixture correntropy in non-Gaussian noise environments exclusively using Doppler measurements. As Doppler measurements are non-linear, a statistical linear regression model is constructed using the unscented transformation. Then, a centralized measurement model is developed, and the mixture correntropy is determined, which contains the high-order statistics of state prediction and the measurement error caused by noise. Then, a robust fusion filter is proposed by maximizing the mixture-correntropy-based cost.

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Jeng, Yih, Hung-Ming Yu, and Chih-Sung Chen. "Algorithm Fusion for 3D Ground-Penetrating Radar Imaging with Field Examples." Remote Sensing 15, no. 11 (2023): 2886. http://dx.doi.org/10.3390/rs15112886.

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Numerous data processing algorithms are available for ground-penetrating radar (GPR) data processing. However, most of the existing processing algorithms are derived from Fourier theory and assume that the system is linear or that data are stationary, which may oversimplify the case. Some nonlinear algorithms are accessible for improvement but generally are for stationary and deterministic systems. To alleviate the dilemma, this study proposes an algorithm fusion scheme that employs standard linear techniques in conjunction with a newer nonlinear and non-stationary method. The linear technique

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Hu, Tao, Xisheng Li, and Jia You. "The weighted fusion prediction algorithm of acoustic interval optimized by PCA-PSO-BP and MLRM." Journal of Physics: Conference Series 2258, no. 1 (2022): 012004. http://dx.doi.org/10.1088/1742-6596/2258/1/012004.

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Abstract Acoustic interval is widely used in drilling operation, but the actual drilling operation is limited by well depth, geological conditions and economic cost, so it is difficult to directly measure the value of acoustic interval. A model between logging data and acoustic interval can be constructed to predict acoustic interval. In view of the shortcomings of traditional algorithms, this paper proposes a weighted fusion algorithm based on the combination optimization of the PCA, PSO, BP and MLRM, carries out the PCA and PSO combination optimization the BP prediction for non-linear loggin

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Tao, Wu, Yong Sheng Xu, and Xiao Yan Wang. "Particle Filtering Algorithm Based on Dynamic Multi-Feature Fusion." Applied Mechanics and Materials 741 (March 2015): 373–77. http://dx.doi.org/10.4028/www.scientific.net/amm.741.373.

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The target tracking technology in image sequence is of great meanings in the military and civilian areas, by using Monte Carlo method to complete the Bayesian recursive, particle filter is widely used in the systems of non-linear and non - Gaussian and good results are gained. However, particle filter there are also disadvantages in terms of sample impoverishment, the choosing of proper proposal distribution, real time and so on. In this paper, the particle filter is utilized to in the feature fusion of the moving target, and the experimental results show that the proposed algorithm has certai

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