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Waveform recognition with application to bar codes
Conference Proceedings 1991 IEEE International Conference on Systems, Man, and Cybernetics, 2002The authors propose that the location and area under a peak can be the features of choice for a waveform recognition system. If the waveform is a result of the convolution of a Gaussian shape point spread function with a bi-level image, the image can be reconstructed by considering the areas under the waveform peaks. This is demonstrated by using a bar
E. Joseph, T. Pavlidis
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Neural Waveform Recognition System
1992Abstract : The Communications Technology Branch in the Command, Control and Communications Directorate of Rome Laboratory performs theoretical research in the area of advanced signal processing as it applies to military communications systems. The research documented in this technical report examines the applicability of neural networks to the ...
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EMG burst waveform recognition procedure
Proceedings of the Fifteenth Annual Northeast Bioengineering Conference, 2003A fast, simple EMG (electromyogram) burst waveform recognition algorithm has been developed for a personal computer. Raw EMG data are detrended, squared, and filtered. A sample EMG waveform segment, known as a template, is drawn from this data. A recognition signal is constructed as the convolution of the template and the prepared EMG data.
G. Dwyer, Y. Noguchi, H.H. Szeto
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Recognition of the Shape of the ST Segment in ECG Waveforms
IEEE Transactions on Biomedical Engineering, 1986A method which recognizes the shape of the ST segment is presented in this paper. This method when applied to an ST segment gives as results: 1) the onset and the end of the ST segment and 2) the equation of a straight line or of a parabola that best approximates this ST segment.
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Recognition memory for arbitrary, complex waveforms
The Journal of the Acoustical Society of America, 1989Recognition memory for arbitrary complex stimuli was measured using the operating characteristic technique developed by Egan [J. P. Egan, AFCRC TN 58-51, AD 152650 (1958)]. Ten complex stimuli (500 ms in duration), each consisting of six, randomly chosen, equal amplitude sinusoidal components spanning frequencies from 300 to 3000 Hz, were used as a ...
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Dual-Waveform Emotion Recognition Model for Conversations
2021 IEEE International Conference on Multimedia and Expo (ICME), 2021Jiayi Zhang +3 more
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Accurate LPI Radar Waveform Recognition With CWD-TFA for Deep Convolutional Network
IEEE Wireless Communications Letters, 2021Van Sang Doan +2 more
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Adversarial unsupervised domain adaptation for cross scenario waveform recognition
Signal Processing, 2020Panfei Du, Jingyu Yang, Xiaofeng Liu
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An Improved LPI Radar Waveform Recognition Framework With LDC-Unet and SSR-Loss
IEEE Signal Processing Letters, 2022Mengmeng Liao, Wangkui Jiang
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