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Image Enhancement Using adaptive Fractional Order filter

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Computer Systems Science & Engineering 2023年第5期45卷 1409-1422页

作者： Ayesha Heena Nagashettappa Biradar Najmuddin M.Maroof Surbhi Bhatia Arwa Mashat Shakila Basheer Department of Electronics and Communication Engineering Bheemanna Khandre Institute of TechnologyBhalkiVisveswaraya Technological UniversityBelagaviIndia Department of Electronics and Communication Engineering Khaja Banda Nawaz College of EngineeringVisveswaraya Technological UniversityBelagaviIndia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl-HofufAl-AhsaSaudi Arabia Faculty of Computing&Information Technology King Abdulaziz UniversityP.O.Box 344Rabigh21911Saudi Arabia Department of Information Systems College of Computer and Information Science Princess Nourah bint Abdulrahman UniversityP.O.BOX 84428Riyadh11671Saudi Arabia

Image enhancement is an important preprocessing task as the contrast is low in most of the medical images,Therefore,enhancement becomes the mandatory process before actual image processing should start.This research article proposes an enhancement of the model-based differential operator for the images in general and Echocardiographic images,the proposed operators are based on Grunwald-Letnikov(G-L),Riemann-Liouville(R-L)and Caputo(Li&Xie),which are the definitions of fractional order calculus.In this fractional-order,differentiation is well focused on the enhancement of echocardiographic images.This provoked for developing a non-linear filter mask for image enhancement.The designed filter is simple and effective in terms of improving the contrast of the input low contrast images and preserving the textural features,particularly in smooth areas.The novelty of the proposed method involves a procedure of partitioning the image into homogenous regions,details,and edges.Thereafter,a fractional differential mask is appropriately chosen adaptively for enhancing the partitioned pixels present in the image.It is also incorporated into the Hessian matrix with is a second-order derivative for every pixel and the parameters such as average gradient and entropy are used for qualitative analysis.The wide range of existing state-of-the-art techniques such as fixed order fractional differential filter for enhancement,histogram equalization,integer-order differential methods have been used.The proposed algorithm resulted in the enhancement of the input images with an increased value of average gradient as well as entropy in comparison to the previous methods.The values obtained are very close(almost equal to 99.9%)to the original values of the average gradient and entropy of the images.The results of the simulation validate the effectiveness of the proposed algorithm.

关键词： adaptive filter differential filter enhancement mask fractional differential mask fractional-order calculus hessian matrix

Distributed adaptive Kalman filter based on variational Bayesian technique

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Control Theory and Technology 2019年第1期17卷 37-47页

作者： Chen HU Xiaoming HU Yiguang HONG Rocket Force University of Engineering Xi'an Shannxi 710025 China epartment of Mathematics Royal Institute of Sweden (KTH) Sweden Institute of Systems Science and University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing 700790 China

In this paper, distributed Kalman filter design is studied for linear dynamics with unknown measurement noise variance, which modeled by Wishart distribution. To solve the problem in a multi-agent network, a distributed adaptive Kalman filter is proposed with the help of variational Bayesian, where the posterior distribution of joint state and noise variance is approximated by a free-form distribution. The con vergence of the proposed algorithm is proved in two main steps: n oise statistics is estimated, where each age nt only use its local information in variational Bayesian expectation (VB-E) step, and state is estimated by a consensus algorithm in variational Bayesian maximum (VB-M) step. Finally, a distributed target tracking problem is investigated with simulations for illustration.

关键词： Distributed Kalman filter adaptive filter multi-agent system variational Bayesian

A new learning statistic for adaptive filter based on predicted residuals

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Progress in Natural Science:Materials International 2006年第8期16卷 833-837页

作者： YANG Yuanxi and GAO Weiguang (Xi’an Research Institute of Surveying and Mapping, Xi’an710054, China Institute of Surveying and Mapping, University of Information Engineering, Zhengzhou 450052, China) Xi'an Research Institute of Surveying and Mapping Xi'an 710054 China Institute of Surveying and Mapping University of Information Engineering Zhengzhou 450052 China

A key problem for an adaptive filter is to establish a suitable adaptive factor for balancing the contributions of the measurements and the predicted state information from some kinematic models. The reasonable adaptive factor needs a reliable learning statistics to judge the state kinematic model errors. After analyzing the existing two kinds of learning statistics based on the state discrepancy and variance component ratio, a new learning statistic based on predicted residuals is set up, which is different from the exiting learning statistics. The new learning statistic does not need to estimate the kinemetic state parameters before the filtering process, Of course, it does not need necessary measurements to estimate state parameters for all observation epochs. The new learning statistic can be applied together with the learning factor constructed by the state discrepancy. The advantages and shortcomings of the new learning factor are analyzed, and an example is given.

关键词： adaptive factor adaptive filter kinematic model predicted residual.

Early Detection of Heartbeat from Multimodal Data Using RPA Learning with KDNN-SAE

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Computer Systems Science & Engineering 2023年第4期45卷 545-562页

作者： A.K.S.Saranya T.Jaya Department of Electronics and Communication Engineering Ponjesly College of EngineeringNagercoilIndia Department of Electronics and Communication Engineering CSI Institute of TechnologyNagercoilIndia

Heartbeat detection stays central to cardiovascular an electrocardiogram(ECG)is used to help with disease diagnosis and management.Existing Convolutional Neural Network(CNN)-based methods suffer from the less generalization problem thus;the effectiveness and robustness of the traditional heartbeat detector methods cannot be guaranteed.In contrast,this work proposes a heartbeat detector Krill based Deep Neural Network Stacked Auto Encoders(KDNN-SAE)that computes the disease before the exact heart rate by combining features from multiple ECG Signals.Heartbeats are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error in classification of heart beat.This work contained Training and testing stages,in the preparation part at first the adaptive filter Enthalpy-based Empirical Mode Decomposition(EMD)is utilized to eliminate the motion artifact in the signal.At that point,the robotic process automation(RPA)learning part extracts the effective features are extracted,and normalized the value of the feature then estimated utilizing the RPA loss function.At last KDNN-SAE prepared training for the data stored in the dataset.In the subsequent stage,input signal compute motion artifact and RPA Learning the evaluation part determines the detection of Heartbeat.So early diagnosis of heart failures is an essential factor.The results of the experiments show that our proposed method has a high score outcome of 0.9997.Comparable to the CIF,which reaches 0.9990.The CNN and Artificial Neural Network(ANN)had less score 0.95115 and 0.90147.

关键词： Deep neural network krill herd optimization stack auto-encoder adaptive filter enthalpy based empirical mode decomposition robotic process automation

adaptive Tracking filter for Stabilizing a Flexible Launch Vehicle

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Computer Aided Drafting,Design and Manufacturing 2004年第2期14卷 71-76页

作者： ALI Mohamed.s.Elmelhi YASIR. Muhammad School of Electrical and Automation Engineering Beijing University of Aeronautics & Astronautics Beijing 100083 ChinaSchool of Electrical and Automation Engineering Beijing University of Aeronautics & Astronautics Beijing 100083 China

The flight control system designer is increasingly concerned with the problem of providing adequate stability of the elastic modes of the flight vehicle. The problem of stabilizing bending modes can be solved by the use of different bending filters. But continuously changing behavior of the elastic modes frequencies makes it impossible to suppress the elastic modes. In this paper, adaptive tracking filter is used to solve this problem. Where it can track the frequency of predominant oscillatory component of its input signal and automatically adjust the shaping characteristics as a function of this frequency. Simulation results are presented to show the frequency tracking accuracy and response of the flight launch vehicle, which are based on the assumption that, only first bending mode is selected at a time. Comparison with the second order band pass filter is carried out in order to emphasis the effectiveness of this design methodology.

关键词： adaptive filter bandpass filter flexible dynamic stabilization.

Impulsive Noise Cancellation in OFDM System Using Low Density Parity Check

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Computer Systems Science & Engineering 2023年第7期46卷 1265-1276页

作者： Attia Irum Abdul Muiz Fayyaz Sara Ayub Mudassar Raza Majed Alhaisoni Muhammad Attique Khan Abdullah Alqahtani Heebum Kim Byeong-Gwon Kang Department of Computer Science University of WahWah Cantt47040Pakistan Balochistan University of Information Technology Engineering and Management SciencesQuettaBalochistan Department of Computer Science COMSATS University IslamabadWah CampusPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of ICT Convergence Soonchunhyang UniversityKorea

An effective communication application necessitates the cancellation of Impulsive Noise(IN)from Orthogonal Frequency Division Multiplexing(OFDM),which is widely used for wireless applications due to its higher data rate and greater spectral efficiency.The OFDM system is typically corrupted by Impulsive Noise,which is an unwanted short-duration pulse with random amplitude and duration.Impulsive noise is created by humans and has non-Gaussian characteristics,causing problems in communication systems such as high capacity loss and poor error rate performance.Several techniques have been introduced in the literature to solve this type of problem,but they still have many issues that affect the performance of the presented methods.As a result,developing a new hybridization-based method is critical for accurate method performance.In this paper,we present a hybrid of a state space adaptive filter and an information coding technique for cancelling impulsive noise from OFDM.The proposed method is also compared to Least Mean Square(LMS),Normalized Least Mean Square(NLMS),and Recursive Least Square(RLS)adaptive filters.It has also been tested using the binary phase-shift keyed(BPSK),four quadrature amplitude modulation(QAM),sixteen QAM,and thirty-two QAM modulation techniques.Bit error Rate(BER)simulations are used to evaluate system performance,and improved performance is obtained.Furthermore,the proposed method is more effective than recent methods.

关键词： Impulsive noise adaptive filter OFDM NLMS RLS

A Family of Partial Update adaptive filter Algorithms in System Identification and Acoustic Echo Cancellation Applications

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A Family of Partial Update Adaptive Filter Algorithms in Sys...

An Improved RLS adaptive filter Algorithm Used to Process Human Body Balance Signal

International Conference on Intelligent Computational Systems(ICICS’2012);International Conference on Mechanical,Automotive and Materials Engineering(ICMAME’2012);International Conference on Electronics,Biomedical Engineering and its Applications(ICEBEA’2012);International Conference on Ecological,Environmental and Biological Sciences(ICEEBS’2012);International Conference on Business,Economics,Management and Behavioral Sciences (ICBEMBS’2012);International Conference on Applied Mathematics and Pharmaceutical Sciences(ICAMPS’2012)

作者： Mohammad Shams Esfand Abadi Behzad Azizian Isaloo Hamid Mohammadi the Shahid Rajaee Teacher Training University Faculty of Electrical and Computer Engineering

The partial update adaptive filters are very useful in different applications of signal processing due to reduction in computational complexity. This paper compares the performance of various partial update adaptive filter algorithms in system identification application. These algorithms are periodic, sequential, and stochastic partial update version of the least mean squares （LMS）, normalized LMS （NLMS）, and affine projection algorithms （APA）. Also, the M-max version of these algorithms is presented. Simulation results show that the partial update adaptive algorithms have comparable performance with the full update adaptive filters. Furthermore, the computational complexity of this family of adaptive filters is lower than full update version of adaptive algorithms.

关键词： adaptive filter partial update computational complexity system identification acoustic echo.

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An Improved RLS Adaptive Filter Algorithm Used to Process Hu...

THE ENGINEER REALIZING OF adaptive NOTCH filter BASE ON MCU

2011 International Conference on Future Computer Science and Education（ICFCSE 2011）

作者： Li Gui-qing Yang JI-mei Li Xiang-chen Gym Teaching & Research Sect.Wuhan Institute of P.E. Wuhan University of Technology China institute of sport science

The human body balance measurement and analysis system ask for high precision to the center of gravity. This article in view of noise filter problem, analyze the insufficiency of commonly used data smoothing method and the classics RLS algorithm, proposed one kind of improved RLS adaptive filtering algorithm, the practical application effect is extremely ideal.

关键词： Human body balance track of center of gravity noise filter adaptive filter

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THE ENGINEER REALIZING OF ADAPTIVE NOTCH FILTER BASE ON MCU