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Noise detection and its removal is very important in the image processing. Detection of noise is very crucial and significant in random valued impulse noise because it does not hamper the image pixels uniformly. This paper presents a novel and unique concept of adaptive dual threshold for the detection of random valued impulse noise along with simple median filter at noise removal stage. Simulation results shows that an efficient noise detection leads to a superior quality of de-noised image as compared to existing adaptive threshold based image de-noising techniques. Proposed threshold computation is based on averaging of pixel values of window which enhances the PSNR of our system as compared to existing median filter based image de-noising methods. 相似文献
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Electrocardiogram is the most commonly used tool for the diagnosis of cardiologic diseases. In order to help cardiologists to diagnose the arrhythmias automatically, new methods for automated, computer aided ECG analysis are being developed. In this paper, a Modified Artificial Bee Colony (MABC) algorithm for ECG heart beat classification is introduced. It is applied to ECG data set which is obtained from MITBIH database and the result of MABC is compared with seventeen other classifier's accuracy.In classification problem, some features have higher distinctiveness than others. In this study, in order to find higher distinctive features, a detailed analysis has been done on time domain features. By using the right features in MABC algorithm, high classification success rate (99.30%) is obtained. Other methods generally have high classification accuracy on examined data set, but they have relatively low or even poor sensitivities for some beat types. Different data sets, unbalanced sample numbers in different classes have effect on classification result. When a balanced data set is used, MABC provided the best result as 97.96% among all classifiers.Not only part of the records from examined MITBIH database, but also all data from selected records are used to be able to use developed algorithm on a real time system in the future by using additional software modules and making adaptation on a specific hardware. 相似文献
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M. Said Ashraf A. M. Khalaf Ashraf 《International Journal of Adaptive Control and Signal Processing》2020,34(3):354-371
An electrocardiogram (ECG) signal is a record of the electrical activities of heart muscle and is used clinically to diagnose heart diseases. An ECG signal should be presented as clear as possible to support accurate decisions made by doctors. This article proposes different combinations of combined adaptive algorithms to derive different noise-cancelling structures to remove (denoise) different kinds of noise from ECG signals. The algorithms are applied to the following types of noise: power line interference, baseline wander, electrode motion artifact, and muscle artifacts. Moreover, the results of the suggested models and algorithms are compared with those of conventional denoising tools such as the discrete wavelet transform, an adaptive filter, and a multilayer neural network (NN) to ensure the superiority of the proposed combined structures and algorithms. Furthermore, the hybrid concept is based on dual, triple, and quadruple combinations of well-known algorithms that derive adaptive filters, such as the least mean squares, normalized least mean squares and recursive least squares algorithms. The combinations are formulated based on partial update, variable step-size (VSS), and second iterative VSS algorithms, which are considered in different combinations. In addition, biased NN and unbiased linear neural network (ULNN) structures are considered. The performance of the different structures and related algorithms are evaluated by measuring the post-signal-to-noise ratio, mean square error, and percentage root mean square difference. 相似文献
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在分析电潜柱塞泵工作原理的基础上,结合柱塞式抽油泵的结构,建立了机组运行的理论示功图,对其进行了深入分析。以功率信号作为故障信息,提出一种基于间接示功图测量的电潜柱塞泵故障诊断方法,并描述了小波去噪方法绘制实测示功图的主要过程。针对机组典型故障,在室内模拟平台和现场油井上对该方法的准确性进行了验证实验与分析。测试结果表明:故障诊断效果较好。 相似文献
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提出一种适合心电信号(ECG)检测的OTA-C滤波器。为了达到低功耗、低截止频率、高直流增益、高阻带衰减、低谐波失真的目的,滤波器采用五阶巴特沃斯全差分低通滤波结构和高增益的两级单端输出OTA,其中OTA电路采用亚阈值区驱动、电流分流和源极负反馈等技术。采用SMIC 0.18-μm 1P6M CMOS工艺进行电路、版图设计及优化。仿真结果表明,滤波器在静态功耗为17.6 μW,截止频率为240 Hz,直流增益为-6 dB,阻带衰减为120 dB每十倍频,三次谐波失真小于-62 dB@ 400 mV,适合应用于心电信号检测模拟前端。 相似文献
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在飞行试验中,由于涡喷发动机遥测数据有限,因此要对其故障进行准确分析定位存在很大难度。利用小波变换对涡喷发动机涡轮转速、喷嘴前压力等遥测数据经过去噪提取后,找出奇异点,并经系统去噪筛选,形成数据文件,利用BP神经网络的模式分类功能,发现故障出现的时刻及部件,并结合研制过程中地面试车数据库,可实现准确定位涡喷发动机故障部位及类型。实际应用证明方法实用有效,可进一步推广到其他系统或部件的故障分析工作中。 相似文献