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Journal articles on the topic 'Adaptive Fuzzy filter'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Aessa, Suad Ali, Ekbal Hussain Ali, Salam Waley Shneen, and Layla H. Abood. "Adaptive Fuzzy Filter Technique for Mixed Noise Removing from Sonar Images Underwater." Journal of Fuzzy Systems and Control 2, no. 2 (2024): 45–49. https://doi.org/10.59247/jfsc.v2i2.176.

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Underwater Analysis of acquired images may be affected by low contrast, haze, and other disturbances., caused by scattering and absorption of the light through propagation. An adaptive fuzzy filter for three mixed noise reduction is adopted on underwater sonar images to take out the various noises that either appear in the image when captured or injected into the image when transmitted. Underwater images when captured usually have speckle noise, salt, pepper noise also Gaussian noise. Is suggested in this paper an adaptive fuzzy filter structure that combines the fuzzy filter, sigmoid sliding

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2

Wang, Yong Jun, Jing Shuo Xu, Rui Hua Song, Yang Gao, and Ya Zhou Di. "Comparison on Three Filter Methods in Self-Alignment for SINS of the Carrier Craft." Advanced Materials Research 591-593 (November 2012): 1793–99. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.1793.

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Fuzzy adaptive filter and H∞ filter are introduced to solve the problem of low filter performance, which comes from uncertain noise caused by seawave and high frequence vibrancy. First, basic principles of the fuzzy adaptive filter and H∞ filter are formulated. Second, state space model of self-alignment for SINS of the carrier craft is built. Finally, according to each character, a comparison on results that Kalman filter, fuzzy adaptive filter and H∞ filter are applied to alignment for SINS of the carrier craft is made. Simulation results show that although Kalman filter has definite robustn

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3

RYU, GEUN-TAEK, DAE-SUNG KIM, DAE-YOUNG LEE, SUNG-HWAN HAN, and HYEON-DEOK BAE. "CONVERGENCE IMPROVEMENT OF ADAPTIVE LATTICE ALGORITHM WITH FUZZY BASED ADAPTIVE GAIN." Journal of Circuits, Systems and Computers 09, no. 01n02 (1999): 125–32. http://dx.doi.org/10.1142/s0218126699000116.

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The choice of the adaptive gain is important to the performance of LMS-based adaptive filters. Depending on application areas, the realization structure of the filters is also important. This letter presents an adaptive lattice algorithm which adjusts the adaptive gain of LMS using fuzzy if-then rules determined by matching input and output variables during adaptation procedure. In each lattice filter stage, this filter adjusts the adaptive gain as the output of the fuzzy logic which has two input variables, normalized squared forward prediction error and one step previous adaptive gain. The p

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4

Xiahua Yang and Peng Seng Toh. "Adaptive fuzzy multilevel median filter." IEEE Transactions on Image Processing 4, no. 5 (1995): 680–82. http://dx.doi.org/10.1109/83.382502.

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García Infante, Juan Carlos, José de J. Medel Juárez, and Juan Carlos Sánchez García. "Neural fuzzy digital filtering: multivariate identifier filters involving multiple inputs and multiple outputs (MIMO)." Ingeniería e Investigación 31, no. 1 (2011): 184–92. http://dx.doi.org/10.15446/ing.investig.v31n1.20569.

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Multivariate identifier filters (multiple inputs and multiple outputs - MIMO) are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter convergence to observable reference system dynamics. One way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. Such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (Shannon, 1948). This paper considers the MIMO digital filter model usi

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Roy, Amarjit, Joyeeta Singha, and Rabul Hussain Laskar. "Removal of Impulse Noise from Gray Images Using Fuzzy SVM Based Histogram Fuzzy Filter." Journal of Circuits, Systems and Computers 27, no. 09 (2018): 1850139. http://dx.doi.org/10.1142/s0218126618501396.

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Impulse noise is an image noise that degrades the quality of the image drastically. In this paper, k-means clustering has been incorporated with fuzzy-support vector machine (FSVM) classifier for classification of noisy and non-noisy pixels in removal of impulse noise from gray images. Here, local binary pattern (LBP) has been incorporated with previously used feature vector prediction error of the processing pixel, absolute difference between median value and processing pixel, median pixel, pixel under operation and mean value around the processing kernel. In this work, [Formula: see text]-me

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Do, Cong Hung, and Huei-Yung Lin. "Incorporating neuro-fuzzy with extended Kalman filter for simultaneous localization and mapping." International Journal of Advanced Robotic Systems 16, no. 5 (2019): 172988141987464. http://dx.doi.org/10.1177/1729881419874645.

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Extended Kalman filter is well-known as a popular solution to the simultaneous localization and mapping problem for mobile robot platforms or vehicles. In this article, the development of a neuro-fuzzy-based adaptive extended Kalman filter technique is presented. The objective is to estimate the proper values of the R matrix at each step. We design an adaptive neuro-fuzzy extended Kalman filter to minimize the difference between the actual and theoretical covariance matrices of the innovation consequence. The parameters of the adaptive neuro-fuzzy extended Kalman filter is then trained offline

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Pulipaka, Krishna Prasad, K. Sathish Kumar, K. Geethali Apoorva, Rohith Rao, and K. Radha Krishna. "Noise Removal from Images Using Adaptive Neuro/Network-Fuzzy Interface Systems." International Journal of Engineering and Applied Technologies 22 (December 13, 2022): 15–32. http://dx.doi.org/10.56431/p-t615v7.

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Any Information signal is best desirable without any external noise/ disturbances. Noise in any signal is the undesirable quantity present which deteriorates the signal's quality, thus compromising the information. Any signal, be it an image signal (2-D) or else a video signal (3-D) in the field of communication, if not always but most number of times prone to noise. In this paper, we would be dealing with removing types of noise on an image, using various filter techniques such as vector median filter, vector directional filter. Using the image processing tools in MATLAB, we could achieve thi

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Salehi, Hadi, Javad Vahidi, and Homayun Motameni. "A Robust Hybrid Filter Based on Evolutionary Intelligence and Fuzzy Evaluation." International Journal of Image and Graphics 18, no. 04 (2018): 1850023. http://dx.doi.org/10.1142/s0219467818500237.

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In this paper, a novel denoising method based on wavelet, extended adaptive Wiener filter and the bilateral filter is proposed for digital images. Production of mode is accomplished by the genetic algorithm. The proposed extended adaptive Wiener filter has been developed from the adaptive Wiener filter. First, the genetic algorithm suggest some hybrid models. The attributes of images, including peak signal to noise ratio, signal to noise ratio and image quality assessment are studied. Then, in order to evaluate the model, the values of attributes are sent to the Fuzzy deduction system. Simulat

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Arnal, Josep, and Luis Súcar. "Hybrid Filter Based on Fuzzy Techniques for Mixed Noise Reduction in Color Images." Applied Sciences 10, no. 1 (2019): 243. http://dx.doi.org/10.3390/app10010243.

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To decrease contamination from a mixed combination of impulse and Gaussian noise on color digital images, a novel hybrid filter is proposed. The new technique is composed of two stages. A filter based on a fuzzy metric is used for the reduction of impulse noise at the first stage. At the second stage, to remove Gaussian noise, a fuzzy peer group method is applied on the image generated from the previous stage. The performance of the introduced algorithm was evaluated on standard test images employing widely used objective quality metrics. The new approach can efficiently reduce both impulse an

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11

Zhao, Yan Jun, and Li LIU. "Optimization and Research of the Adaptive Wiener Filter Based on Fuzzy Neural Networks." Applied Mechanics and Materials 411-414 (September 2013): 1660–64. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1660.

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This paper introduces fuzzy neural network technology into the adaptive filter and makes further research on its structure and algorithms. At first, fuzzy rules are determined and the network structure is built by means of dividing fuzzy subspaces. Secondly, membership functions are chosen layers are defined and the network is trained by adaptive learning algorithm. Thirdly, training error is the minimum with repeating debugging. Finally, linking weight, the central value and width of the network membership function is adjusted by using experience of experts. The optimal performance of Adaptiv

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Suneetha, Akula, and E. Srinivasa Reddy. "Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter." Journal of Intelligent Systems 30, no. 1 (2020): 240–57. http://dx.doi.org/10.1515/jisys-2019-0211.

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Abstract In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set fi

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Ahn, Dong Jun, Keun Sik Kim, Hyun Do Nam, and Eun Woo Shin. "Multi-Channel Active Noise Control System Designs with Fuzzy Logic Stabilized Algorithms." Advanced Engineering Forum 2-3 (December 2011): 96–101. http://dx.doi.org/10.4028/www.scientific.net/aef.2-3.96.

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In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal ca

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Mohaideen Abdul Kadhar, K., S. Rengarajan, S. Tamilselvi, et al. "Finite Impulse Response Filter Design Using Fuzzy Logic-Based Diversity-Controlled Self-Adaptive Differential Evolution." International Transactions on Electrical Energy Systems 2023 (July 13, 2023): 1–18. http://dx.doi.org/10.1155/2023/1572996.

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The design of finite impulse response (FIR) filters involves the estimation of effective filter coefficients, making the designed filter exhibit infinite stopband attenuation and have a flat-shaped passband. The few conventional filter design methods such as impulse response truncation (IRT) and windowing technique exhibit undesirable characteristics owing to the Gibbs phenomenon, thus making them unsuitable for various practical complexities. This research work employs the fuzzy logic-based diversity-controlled self-adaptive differential evolution algorithm (FLDCSaDE) for the design of FIR ba

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15

Fei, Juntao, and Shixi Hou. "Adaptive Fuzzy Control with Supervisory Compensator for Three-Phase Active Power Filter." Journal of Applied Mathematics 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/654937.

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An adaptive fuzzy control system with supervisory controller is proposed to improve dynamic performance of three-phase active power filter (APF). The proposed adaptive fuzzy controller for APF does not build an accurate mathematical model but approximates the nonlinear characteristics of APF using fuzzy approximation. The adaptive law based on the Lyapunov analysis can adaptively adjust the fuzzy rules; therefore the asymptotical stability of the adaptive fuzzy control system can be guaranteed. Simulation results demonstrate that the APF control system has excellent dynamic performance such as

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16

Morillas, Samuel. "New adaptive vector filter using fuzzy metrics." Journal of Electronic Imaging 16, no. 3 (2007): 033007. http://dx.doi.org/10.1117/1.2767335.

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17

Ki Yong Lee. "Complex fuzzy adaptive filter with LMS algorithm." IEEE Transactions on Signal Processing 44, no. 2 (1996): 424–27. http://dx.doi.org/10.1109/78.485938.

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18

Zhang, Weiping, Mohit Kumar, Jingzhi Yang, Yunfeng Zhou, and Yihua Mao. "An adaptive fuzzy filter for image denoising." Cluster Computing 22, S6 (2018): 14107–24. http://dx.doi.org/10.1007/s10586-018-2253-5.

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19

Demirci, Recep. "Fuzzy adaptive anisotropic filter for medical images." Expert Systems 27, no. 3 (2010): 219–29. http://dx.doi.org/10.1111/j.1468-0394.2010.00525.x.

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Salehi, Hadi, and Javad Vahidi. "An Ultrasound Image Despeckling Method Based on Weighted Adaptive Bilateral Filter." International Journal of Image and Graphics 20, no. 03 (2020): 2050020. http://dx.doi.org/10.1142/s0219467820500205.

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Images are widely used in engineering. Unfortunately, ultrasound images are mainly degraded by an intrinsic noise called speckle. Therefore, de-speckling is a critical preprocessing step. Therefore, a robust despeckling method and accurate evaluation of images are suggested. We suggest three phases and a three-step denoising filter. In the first phase, the coefficients of variation are computed from the noisy image. The second phase is a three-step denoising filter. The first step is denoising of extreme levels of homogeneous regions, based on fuzzy homogeneous regions. The second step is a pr

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21

Ma, Zhiyao, and Ke Sun. "Nonlinear Filter-Based Adaptive Output-Feedback Control for Uncertain Fractional-Order Nonlinear Systems with Unknown External Disturbance." Fractal and Fractional 7, no. 9 (2023): 694. http://dx.doi.org/10.3390/fractalfract7090694.

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This study is devoted to a nonlinear filter-based adaptive fuzzy output-feedback control scheme for uncertain fractional-order (FO) nonlinear systems with unknown external disturbance. Fuzzy logic systems (FLSs) are applied to estimate unknown nonlinear dynamics, and a new FO fuzzy state observer based on a nonlinear disturbance observer is established for simultaneously estimating the unmeasurable states and mixed disturbance. Then, with the aid of auxiliary functions, a novel FO nonlinear filter is given to approximately replace the virtual control functions, together with the corresponding

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22

Sąsiadek, Jurek, and Hamdan Bitlmal. "Optimal State Estimation via Adaptive Fuzzy Particle Filter." Pomiary Automatyka Robotyka 27, no. 4 (2023): 5–12. http://dx.doi.org/10.14313/par_250/5.

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Particle Filters (PF) accomplish nonlinear system estimation and have received high interest from numerous engineering domains over the past decade. The main problem of PF is to degenerate over time due to the loss of particle diversity. One of the essential causes of losing particle diversity is sample impoverishment (most of particle’s weights are insignificant) which affects the result from the particle depletion in the resampling stage and unsuitable prior information of process and measurement noise. To address this problem, a new Adaptive Fuzzy Particle Filter (AFPF) is used to improve t

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Shaik Nagul Sharif and Sri Latha Veerla. "Intelligent Hybrid-Fuzzy Controller using VLLMS Based Shunt Active Filter." International Journal for Modern Trends in Science and Technology 06, no. 09 (2020): 215–29. http://dx.doi.org/10.46501/ijmtst060933.

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The power quality problem in the power system is increased with the use of non-linear devices. Due to the use of non-linear devices like power electronic converters, there is an increase in harmonic content in the source current. Due to this there is an increase in the losses, instability and poor voltage waveform. To mitigate the harmonics and provide the reactive power compensation, we use filters. There are different filters used in the power system. Passive filters provide limited compensation, so active filters can be used for variable compensation. In this work, a shunt active filter has

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Odry, Ákos, Istvan Kecskes, Peter Sarcevic, Zoltan Vizvari, Attila Toth, and Péter Odry. "A Novel Fuzzy-Adaptive Extended Kalman Filter for Real-Time Attitude Estimation of Mobile Robots." Sensors 20, no. 3 (2020): 803. http://dx.doi.org/10.3390/s20030803.

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This paper proposes a novel fuzzy-adaptive extended Kalman filter (FAEKF) for the real-time attitude estimation of agile mobile platforms equipped with magnetic, angular rate, and gravity (MARG) sensor arrays. The filter structure employs both a quaternion-based EKF and an adaptive extension, in which novel measurement methods are used to calculate the magnitudes of system vibrations, external accelerations, and magnetic distortions. These magnitudes, as external disturbances, are incorporated into a sophisticated fuzzy inference machine, which executes fuzzy IF-THEN rules-based adaption laws

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González-Hidalgo, Manuel, Sebastia Massanet, Arnau Mir, and Daniel Ruiz-Aguilera. "Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density." Applied Sciences 11, no. 2 (2021): 560. http://dx.doi.org/10.3390/app11020560.

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Many computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arithmetic mean aggregation function and the fuzzy mathematical morphology is proposed. The performance of the proposed filter is highly competitive when compared with other state-of-the-art filters regardless of the amount of salt-and-pepper noise present in the image, achieving notable results for any

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González-Hidalgo, Manuel, Sebastia Massanet, Arnau Mir, and Daniel Ruiz-Aguilera. "Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density." Applied Sciences 11, no. 2 (2021): 560. http://dx.doi.org/10.3390/app11020560.

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Many computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arithmetic mean aggregation function and the fuzzy mathematical morphology is proposed. The performance of the proposed filter is highly competitive when compared with other state-of-the-art filters regardless of the amount of salt-and-pepper noise present in the image, achieving notable results for any

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Rudnitskii, A. G., M. A. Rudnytska, L. V. Tkachenko, and E. D. Pechuk. "Application of fuzzy logic in finding the optimal filter in optoacoustics problems." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 1 (2021): 43–54. http://dx.doi.org/10.17721/1812-5409.2021/1.5.

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Denoising is an important step in the early stage of signal preprocessing in optoacoustic applications. The efficiency of such modern noise removal methods as wavelet or curvlet filtering depends significantly on the numerical combinations and forms of wavelet transform parameters, and the multidimensional extension of such filters is rather non-trivial. These issues are serious obstacle for using of these highly effective filters in the tasks of optoacoustic reconstruction, especially in real laboratorial or medical practice. The objective of our study was to find the optimal filter, convenie

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Ali, Ekbal Hussain, Ahmed Hameed Reja, and Layla H. Abood. "Design hybrid filter technique for mixed noise reduction from synthetic aperture radar imagery." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1325–31. http://dx.doi.org/10.11591/eei.v11i3.3708.

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For military and civilian applications, synthetic aperture radar (SAR) imaging is an essential instrument for obtaining images of the Earth's surface. Speckle noise, a form of noise that is multiplicative, generated by conflicting echoes returned from each pixel, has a significant impact on the SAR picture. On SAR pictures, a hybrid filter for mixed noise reduction is used to remove the mixed noises that are present in the data during capture and transmission. Specifically, speckle noise and salt and pepper noises from SAR images. Both are being worked on at the same time to minimize mixed noi

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Ekbal, Hussain Ali, Hameed Reja Ahmed, and H. Abood Layla. "Design hybrid filter technique for mixed noise reduction from synthetic aperture radar imagery." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1325~1331. https://doi.org/10.11591/eei.v11i3.3708.

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For military and civilian applications, synthetic aperture radar (SAR) imaging is an essential instrument for obtaining images of the Earth's surface. Speckle noise, a form of noise that is multiplicative, generated by conflicting echoes returned from each pixel, has a significant impact on the SAR picture. On SAR pictures, a hybrid filter for mixed noise reduction is used to remove the mixed noises that are present in the data during capture and transmission. Specifically, speckle noise and salt and pepper noises from SAR images. Both are being worked on at the same time to minimize mixed

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Tehrani, Mohammad, Nader Nariman-zadeh, and Mojtaba Masoumnezhad. "Adaptive fuzzy hybrid unscented/H-infinity filter for state estimation of nonlinear dynamics problems." Transactions of the Institute of Measurement and Control 41, no. 6 (2018): 1676–85. http://dx.doi.org/10.1177/0142331218787607.

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In this paper, a new hybrid unscented Kalman (UKF) and unscented [Formula: see text](U[Formula: see text]F) filter is presented that can adaptively adjust its performance better than that of either UKF and/or U[Formula: see text], accordingly. In this way, two Takagi-Sugeno-Kang (TSK) fuzzy logic systems are presented to adjust automatically some weights that combine those UK and U[Formula: see text] filters, independent of the dynamics of the problem. Such adaptive fuzzy hybrid unscented Kalman/[Formula: see text] filter (AFUK[Formula: see text]) is based on the combination of gain, a priori

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31

Chau, Minh Thuyen. "Adaptive Current Control Method for Hybrid Active Power Filter." Journal of Electrical Engineering 67, no. 5 (2016): 343–50. http://dx.doi.org/10.1515/jee-2016-0049.

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AbstractThis paper proposes an adaptive current control method for Hybrid Active Power Filter (HAPF). It consists of a fuzzy-neural controller, identification and prediction model and cost function. The fuzzy-neural controller parameters are adjusted according to the cost function minimum criteria. For this reason, the proposed control method has a capability on-line control clings to variation of the load harmonic currents. Compared to the single fuzzy logic control method, the proposed control method shows the advantages of better dynamic response, compensation error in steady-state is small

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PHAM, TUAN D., and MICHAEL WAGNER. "IMAGE ENHANCEMENT BY KRIGING AND FUZZY SETS." International Journal of Pattern Recognition and Artificial Intelligence 14, no. 08 (2000): 1025–38. http://dx.doi.org/10.1142/s0218001400000659.

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A kriging method is presented as a spatial filter for smoothing gray-scale images degraded by Gaussian white noise. The concepts are based on the analysis of semivariances, the linear combination scheme of kriging, and fuzzy sets. Application of fuzzy sets allows a gradual transition between two boundaries of semivariance levels as a criterion for smoothing the pixel values. This fuzzy thresholding also allows some degree of flexibility to suit various desired results for particular problems. Experimental results obtained by the fuzzy kriging filter are smoother and still preserve edges compar

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Lee, Ching-Hung, and Yu-Ching Lin. "An adaptive neuro-fuzzy filter design via periodic fuzzy neural network." Signal Processing 85, no. 2 (2005): 401–11. http://dx.doi.org/10.1016/j.sigpro.2004.09.011.

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Chin-Teng Lin and Chia-Feng Juang. "An adaptive neural fuzzy filter and its applications." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 27, no. 4 (1997): 635–56. http://dx.doi.org/10.1109/3477.604107.

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Meher, Saroj K., and Brijraj Singhawat. "Adaptive, Noise-Exclusive and Assessment-Based Fuzzy Switching Median Filter For High Intensity Impulse Noise." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 23, no. 06 (2015): 949–63. http://dx.doi.org/10.1142/s0218488515500439.

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The article proposes an adaptive, noise-exclusive and assessment-based fuzzy switching median filter for high intensity impulse noise. The filter adaptively changes the size of sliding window in accordance with noise intensity and noise-exclusive operation is performed only on noise-free pixels. These steps thus preserve the image details effectively. Judicious assessment of the previously restored pixels is made in order to use them in replacing the noisy pixels and further improve the efficiency of filter. With these possibilities, fuzzy switching median filter-based approach is also incorpo

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Mitsunaga, Kouichi, and Takami Matsuo. "Adaptive Compensation of Friction Forces with Differential Filter." International Journal of Computers Communications & Control 3, no. 1 (2008): 80. http://dx.doi.org/10.15837/ijccc.2008.1.2377.

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In this paper, we design an adaptive controller to compensate the nonlinear friction model when the output is the position. First, we present an adaptive differential filter to estimate the velocity. Secondly, the dynamic friction force is compensated by a fuzzy adaptive controller with position measurements. Finally, a simulation result for the proposed controller is demonstrated.

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Gong, Lei, Wenjuan Luo, Yu Li, Jingwen Chen, and Zhiguang Hua. "Rotor Unbalanced Vibration Control of Active Magnetic Bearing High-Speed Motor via Adaptive Fuzzy Controller Based on Switching Notch Filter." Applied Sciences 15, no. 7 (2025): 3681. https://doi.org/10.3390/app15073681.

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This paper proposes an adaptive fuzzy controller based on a switching notch filter to address the rotor unbalance vibration control problem of an active magnetic bearing (AMB) high-speed motor system in the full rotational speed range. Aiming at the complex nonlinear and time-varying characteristics of the AMB rigid rotor system, this study designs an adaptive fuzzy controller (AFC) that obtains fuzzy quantities by blurring the rotor vibration information and vibration rate of change as the input signals and then obtains the fuzzy set through fuzzy reasoning and modifies the parameters of the

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Fei, Juntao, Kaiqi Ma, Shenglei Zhang, Weifeng Yan, and Zhuli Yuan. "Adaptive Current Control with PI-Fuzzy Compound Controller for Shunt Active Power Filter." Mathematical Problems in Engineering 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/546842.

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An adaptive control technology and PI-fuzzy compound control technology are proposed to control an active power filter (APF). AC side current compensation and DC capacitor voltage tracking control strategy are discussed and analyzed. Model reference adaptive controller for the AC side current compensation is derived and established based on Lyapunov stability theory; proportional and integral (PI) fuzzy compound controller is designed for the DC side capacitor voltage control. The adaptive current controller based on PI-fuzzy compound system is compared with the conventional PI controller for

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M, Suriya Priyadharsini, and G. R. Sathiaseelan J. "The New Robust Adaptive Median Filter for Denoising Cancer Images Using Image Processing Techniques." Indian Journal of Science and Technology 16, no. 35 (2023): 2813–21. https://doi.org/10.17485/IJST/v16i35.1024.

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Abstract <strong>Background/Objectives:</strong> One of the leading causes of death for women is breast cancer, and extensive research has been conducted to improve the diagnosis and detection of breast cancer using various image processing techniques. Medical imaging plays a crucial role in this domain, particularly mammography, which is widely used for breast cancer screening and diagnosis. This paper introduces a novel filtering technique called the New Robust Adaptive Median Filter (RAMF). <strong>Method:</strong> The suggested approach only takes into account noise-free pix

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Liu, Zhi, Qi Hang Wu, and Yun Zhang. "Data-Based Adaptive Fuzzy Wavelet Filter for Robot-Assisted System." Advanced Materials Research 255-260 (May 2011): 1994–98. http://dx.doi.org/10.4028/www.scientific.net/amr.255-260.1994.

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One of the main problems for effective control of a minimally invasive surgery (MIS) is the imprecision that caused by hand tremor. In this paper, a new kind of nonlinear adaptive filter, the fuzzy wavelet neural network filter (FWNNF), is proposed to alleviate this problem. With the FWNNF, we can model and predict the hand tremor more effectively and improve the precision and reliability in the robot-assisted system for microsurgery. Extensive simulation results demonstrate the effectiveness of the proposed filter and its superior performance over its competing rivals.

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Harkouss, Youssef. "Accurate modeling and optimization of microwave circuits and devices using adaptive neuro-fuzzy inference system." International Journal of Microwave and Wireless Technologies 3, no. 6 (2011): 637–45. http://dx.doi.org/10.1017/s1759078711000651.

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In this paper, an accurate neuro-fuzzy-based model is proposed for efficient computer-aided design (CAD) modeling and optimization of microwave circuits and devices. The adaptive neuro-fuzzy inference system (ANFIS) approach is used to determine the scattering parameters of a microstrip filter and is applied to the optimization design of this microstrip filter. The ANFIS has the advantages of expert knowledge of fuzzy inference system and learning capability of artificial neural networks. The neuro-fuzzy model has been trained and tested with different sets of input/output data. Finally, diffe

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Jwo, Dah-Jing, and Shih-Yao Lai. "Navigation Integration Using the Fuzzy Strong Tracking Unscented Kalman Filter." Journal of Navigation 62, no. 2 (2009): 303–22. http://dx.doi.org/10.1017/s037346330800516x.

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A navigation integration processing scheme, called the strong tracking unscented Kalman filter (STUKF), is based on the combination of an unscented Kalman filter (UKF) and a strong tracking filter (STF). The UKF employs a set of sigma points by deterministic sampling, such that the linearization process is not necessary, and therefore the error caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. As a type of adaptive filter, the STF is essentially a nonlinear smoother algorithm that employs suboptimal multiple fading factors, in which the softening factor

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43

Sushmithawathi, K., and P. Indra. "Extraction of significant features using GLDM for Covid-19 prediction." Journal of Trends in Computer Science and Smart Technology 3, no. 4 (2022): 287–93. http://dx.doi.org/10.36548/jtcsst.2021.4.004.

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Although Covid-19 caused by the SARS-COV-2 virus, is a deadliest disease, many people experienced mild symptoms and were recovered soon. In this paper, coronavirus can be easily detected using CT scan images of affected patients. Initially, images are pre-processed by filters like Median filter and Noise adaptive fuzzy switching median filter, and then the quality measurements like MSE, and PSNR are calculated. After preprocessing, segmentation is done by K-means and Robust self sparse fuzzy clustering algorithm, and then the parameters like LMSE and NAE are calculated. Finally, to get optimum

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44

Sushmithawathi, K., and P. Indra. "Extraction of significant features using GLDM for Covid-19 prediction." Journal of Trends in Computer Science and Smart Technology 3, no. 4 (2022): 287–93. http://dx.doi.org/10.36548/jtcsst.2021.4.004.

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Abstract:

Although Covid-19 caused by the SARS-COV-2 virus, is a deadliest disease, many people experienced mild symptoms and were recovered soon. In this paper, coronavirus can be easily detected using CT scan images of affected patients. Initially, images are pre-processed by filters like Median filter and Noise adaptive fuzzy switching median filter, and then the quality measurements like MSE, and PSNR are calculated. After preprocessing, segmentation is done by K-means and Robust self sparse fuzzy clustering algorithm, and then the parameters like LMSE and NAE are calculated. Finally, to get optimum

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45

Habib, Muhammad, Ayyaz Hussain, Eid Rehman, et al. "Convolved Feature Vector Based Adaptive Fuzzy Filter for Image De-Noising." Applied Sciences 13, no. 8 (2023): 4861. http://dx.doi.org/10.3390/app13084861.

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In this paper, a convolved feature vector based adaptive fuzzy filter is proposed for impulse noise removal. The proposed filter follows traditional approach, i.e., detection of noisy pixels based on certain criteria followed by filtering process. In the first step, proposed noise detection mechanism initially selects a small layer of input image pixels, convolves it with a set of weighted kernels to form a convolved feature vector layer. This layer of features is then passed to fuzzy inference system, where fuzzy membership degrees and reduced set of fuzzy rules play an important part to clas

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Serkies, Piotr J., and Krzysztof Szabat. "Fuzzy adaptive Kalman filter for the drive system with an elastic coupling." Archives of Electrical Engineering 62, no. 2 (2013): 251–65. http://dx.doi.org/10.2478/aee-2013-0020.

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Abstract In the paper issues related to the design of a robust adaptive fuzzy estimator for a drive system with a flexible joint is presented. The proposed estimator ensures variable Kalman gain (based on the Mahalanobis distance) as well as the estimation of the system parameters (based on the fuzzy system). The obtained value of the time constant of the load machine is used to change the values in the system state matrix and to retune the parameters of the state controller. The proposed control structure (fuzzy Kalman filter and adaptive state controller) is investigated in simulation and ex

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Zhang, Lan Ying, and Hai Yang Liu. "Adaptive Bandwidth PLL Design Based on Fuzzy Logic Control." Applied Mechanics and Materials 543-547 (March 2014): 1393–96. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1393.

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Based on fuzzy logic control adaptive bandwidth PLL design is presented for the problem of tracking poor stability and low accuracy when a certain type of radar tracking dynamic spacecraft. This method is mainly through fuzzy logic controller, adaptive level is determined by control rule of input respectively, and the outputs of rules are weighted combined to control the coefficient of loop filter, thus adjusting automatically the loop bandwidth, and enhancing the tracking stability of radar equipment and improving ranging accuracy. The simulation results show that the fuzzy logic control adap

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Guo, Bei Tao. "Application of Adaptive Fuzzy Filter in Ultrasonic Test System." Advanced Materials Research 712-715 (June 2013): 1970–73. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.1970.

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In order to avoid some shortcomings such as poor accuracy and low signal-to-noise ration, an ultrasonic test system based on automatic and intelligent testing are introduced. After ultrasonic signal is transmitted and received; data processing, data saving and curve displaying are performed in this test system. To solve the problem of extracting the weak ultrasonic signals from the strong noise, an adaptive filter based on least-mean-square (LMS) algorithm is designed. The convergence factor of the algorithm is chose according adaptive fuzzy control rule. Experimental results show that the fil

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Diaz-Mendez, Alejandro, Hector Manuel Perez-Meana, Juan Carlos Sanchez-Garcia, and Gonzalo Duchen Sanchez. "A VLSI Analog Adaptive Filter Using Fuzzy Logic Adaptation." Telecommunications and Radio Engineering 56, no. 1 (2001): 12. http://dx.doi.org/10.1615/telecomradeng.v56.i1.90.

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Tseng, Chien-Hao, Sheng-Fuu Lin, and Dah-Jing Jwo. "Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems." Sensors 16, no. 8 (2016): 1167. http://dx.doi.org/10.3390/s16081167.

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