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Journal articles on the topic '2-D Signals'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 September 2023

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1

Sathyanarayana, P., P. S. Reddy, and M. N. S. Swamy. "Interpolation of 2-D signals." IEEE Transactions on Circuits and Systems 37, no. 5 (1990): 623–25. http://dx.doi.org/10.1109/31.54999.

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2

Maharana, G. S., and P. K. Meher. "Interpolation of 2-D Signals using 2-D Hartley-like Transform." IETE Journal of Research 43, no. 4 (1997): 333–35. http://dx.doi.org/10.1080/03772063.1997.11415997.

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3

Stoica, P., and Jian Li. "On eigenpolynomials for 2-D sinusoidal signals." IEEE Signal Processing Letters 6, no. 1 (1999): 11–12. http://dx.doi.org/10.1109/97.736238.

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4

Sole, A. F., Shing-Chung Ngan, G. Sapiro, Xiaoping Hu, and A. Lopez. "Anisotropic 2-D and 3-D averaging of fMRI signals." IEEE Transactions on Medical Imaging 20, no. 2 (2001): 86–93. http://dx.doi.org/10.1109/42.913175.

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5

Pogribny, W. A. "1-D and 2-D signals parallel processing in mixed formats." Radioelectronics and Communications Systems 55, no. 3 (2012): 115–23. http://dx.doi.org/10.3103/s0735272712030028.

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6

Friedlander, B., and J. M. Francos. "Model based phase unwrapping of 2-D signals." IEEE Transactions on Signal Processing 44, no. 12 (1996): 2999–3007. http://dx.doi.org/10.1109/78.553474.

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7

Li, Wenzhe, and Alfred Fettweis. "Interpolation filters for 2-D hexagonally sampled signals." International Journal of Circuit Theory and Applications 25, no. 4 (1997): 259–77. http://dx.doi.org/10.1002/(sici)1097-007x(199707/08)25:4<259::aid-cta962>3.0.co;2-9.

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8

Mertzios, B. G. "Block parallel processing of 2-D digital signals." International Journal of Circuit Theory and Applications 14, no. 3 (1986): 211–28. http://dx.doi.org/10.1002/cta.4490140304.

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9

de Beer, R., D. van Ormondt, and W. W. F. Pijnappel. "Quantification of 1-D and 2-D magnetic resonance time domain signals." Pure and Applied Chemistry 64, no. 6 (1992): 815–23. http://dx.doi.org/10.1351/pac199264060815.

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10

Fish, S. M., and M. J. Bosma. "Abnormal deletions in the T-cell receptor delta locus of mouse thymocytes." Molecular and Cellular Biology 14, no. 7 (1994): 4455–64. http://dx.doi.org/10.1128/mcb.14.7.4455-4464.1994.

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Separate genetic elements (V, D, and J) encode the variable regions of lymphocyte antigen receptors. During early lymphocyte differentiation, these elements rearrange to form contiguous coding segments (VJ and VDJ) for a diverse array of variable regions. Rearrangement is mediated by a recombinase that recognizes short DNA sequences (signals) flanking V, D, and J elements. Signals flank both the 5' and 3' sides of each D element, thereby allowing assembly of a functional VDJ gene. However, in rearrangements involving the D delta 2 and J delta 1 elements of the mouse T-cell receptor delta (TCR delta) locus, we unexpectedly found that the D delta 2 element and a portion of its 5' signal are often deleted. Approximately 50% of recovered D delta 2 to J delta 1 rearrangements from thymocytes of adult wild-type mice showed such deletions. An additional 20% of the rearrangements contained standard D delta 2-J delta 1 coding junctions but showed some loss of nucleotides from the 5' D delta 2 signal. This loss was clearly associated with another event involving a site-specific cleavage at the 5' signal/coding border of D delta 2 and rejoining of the modified signal and coding ends. The abnormal loss of D delta 2 and a portion of the 5' D delta 2 signal was infrequently observed in D delta 2-to-J delta 1 rearrangements recovered from neonatal mice. The possible basis and significance of this age-dependent phenomenon are discussed.

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11

Fish, S. M., and M. J. Bosma. "Abnormal deletions in the T-cell receptor delta locus of mouse thymocytes." Molecular and Cellular Biology 14, no. 7 (1994): 4455–64. http://dx.doi.org/10.1128/mcb.14.7.4455.

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Separate genetic elements (V, D, and J) encode the variable regions of lymphocyte antigen receptors. During early lymphocyte differentiation, these elements rearrange to form contiguous coding segments (VJ and VDJ) for a diverse array of variable regions. Rearrangement is mediated by a recombinase that recognizes short DNA sequences (signals) flanking V, D, and J elements. Signals flank both the 5' and 3' sides of each D element, thereby allowing assembly of a functional VDJ gene. However, in rearrangements involving the D delta 2 and J delta 1 elements of the mouse T-cell receptor delta (TCR delta) locus, we unexpectedly found that the D delta 2 element and a portion of its 5' signal are often deleted. Approximately 50% of recovered D delta 2 to J delta 1 rearrangements from thymocytes of adult wild-type mice showed such deletions. An additional 20% of the rearrangements contained standard D delta 2-J delta 1 coding junctions but showed some loss of nucleotides from the 5' D delta 2 signal. This loss was clearly associated with another event involving a site-specific cleavage at the 5' signal/coding border of D delta 2 and rejoining of the modified signal and coding ends. The abnormal loss of D delta 2 and a portion of the 5' D delta 2 signal was infrequently observed in D delta 2-to-J delta 1 rearrangements recovered from neonatal mice. The possible basis and significance of this age-dependent phenomenon are discussed.

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12

MIKHAEL, WASFY B., and HAOPING YU. "ADAPTIVE, FREQUENCY DOMAIN, 2-D MODELING USING SPATIOTEMPORAL SIGNALS." Journal of Circuits, Systems and Computers 06, no. 04 (1996): 351–58. http://dx.doi.org/10.1142/s0218126696000236.

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In this paper, an adaptive, frequency domain, steepest descent algorithm for two-dimensional (2-D) system modeling is presented. Based on the equation error model, the algorithm, which characterizes the 2-D spatially linear and invariant unknown system by a 2-D auto-regressive, moving-average (ARMA) process, is derived and implemented in the 3-D spatiotemporal domain. At each iteration, corresponding to a given pair of input and output 2-D signals, the algorithm is formulated to minimize the error-function’s energy in the frequency domain by adjusting the 2-D ARMA model parameters. A signal dependent, optimal convergence factor, referred to as the homogeneous convergence factor, is developed. It is the same for all the coefficients but is updated once per iteration. The resulting algorithm is called the Two-Dimensional, Frequency Domain, with Homogeneous µ*, Adaptive Algorithm (2D-FD-HAA). In addition, the algorithm is implemented using the 2-D Fast Fourier Transform (FFT) to enhance the computational efficiency. Computer simulations demonstrate the algorithm’s excellent adaptation accuracy and convergence speed. For illustration, the proposed algorithm is successfully applied to modeling a time varying 2-D system.

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13

Liu, F. "Synthesis of 2-D fractal signals based on wavelets." IEICE Electronics Express 5, no. 2 (2008): 81–86. http://dx.doi.org/10.1587/elex.5.81.

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14

Rao, C. R., Lincheng Zhao, and Bin Zhou. "Maximum likelihood estimation of 2-D superimposed exponential signals." IEEE Transactions on Signal Processing 42, no. 7 (1994): 1795–802. http://dx.doi.org/10.1109/78.298285.

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15

Friedlander, B., and J. M. Francos. "An estimation algorithm for 2-D polynomial phase signals." IEEE Transactions on Image Processing 5, no. 6 (1996): 1084–87. http://dx.doi.org/10.1109/83.503925.

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16

Marvasti, Farokh A. "Interpolation of 2-D signals from their isolated zeros." Multidimensional Systems and Signal Processing 1, no. 1 (1990): 87–97. http://dx.doi.org/10.1007/bf01812209.

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17

Mohan, N. L., and L. Anand Babu. "An analysis of 3-D analytic signal." GEOPHYSICS 60, no. 2 (1995): 531–36. http://dx.doi.org/10.1190/1.1443790.

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The mathematical and physical basis of defining the 3-D analytic function and the corresponding analytic signal is critically examined, and it is proved that 3-D analytic signals based on (1) scalar and (2) vector additions of the horizontal derivatives of the total magnetic fields are completely identical. Two sets of simulated gridded data are considered, and 3-D analytic signals are computed using both scalar and vector additions and are found to be identical. The equality of scalar and vector additions of 3-D analytic signals is further demonstrated with the help of gridded‐surface vertical magnetic field data from the Krishna‐Godavari Basin, Andhra Pradesh, India.

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18

Ouahabi, A., and S. Femmam. "Wavelet-based multifractal analysis of 1-D and 2-D signals: New results." Analog Integrated Circuits and Signal Processing 69, no. 1 (2011): 3–15. http://dx.doi.org/10.1007/s10470-011-9620-y.

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19

Li, Xiangzhi, Weijia Cui, Haiyun Xu, et al. "Joint 2-D angles and time delay estimation of coherent wideband signals." MATEC Web of Conferences 309 (2020): 01006. http://dx.doi.org/10.1051/matecconf/202030901006.

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Joint direction of arrival (DOA) and time delay (TD) estimation of wideband signals such as WIFI and mobile communication signals has to face the challenges aroused by multipath effect in indoor environments. New methods that can deal with coherent wideband signals with high estimation accuracy are necessary. To achieve localization when signals are coherent, this paper proposes a new joint estimation method which fully utilizes the subcarriers of wideband signals. This method could greatly extend the array aperture and accomplish the joint estimation through UCA-ESPRIT and one-dimensional (1-D) search. Simulation experiments are conducted to show the validity and efficiency of this method.

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20

Fu, Zewen, Hengrui Zhang, Jianhui Zhao, Ning Li, and Fengbin Zheng. "A Modified 2-D Notch Filter Based on Image Segmentation for RFI Mitigation in Synthetic Aperture Radar." Remote Sensing 15, no. 3 (2023): 846. http://dx.doi.org/10.3390/rs15030846.

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Synthetic aperture radar (SAR), as an active microwave sensor, can inevitably receive radio frequency interference (RFI) generated by various electromagnetic equipment. When the SAR system receives RFI, it will affect SAR imaging and limit the application of SAR images. As a kind of RFI mitigation method, notch filtering method is a classical method with high efficiency and robust performance. However, the notch filtering methods pay no attention to the protection of useful signals. This paper proposed a modified 2-D notch filter based on image segmentation for RFI mitigation with signal-protected capability. (1) The adaptive gamma correction (AGC) approach was utilized to enhance the SAR image with RFI in the range-frequency and azimuth-time domain. (2) The modified selective binary and Gaussian filtering regularized level set (SBGFRLS) model was utilized to further process the image after AGC to accurately extract the contour of the useful signals with interference, which is more conducive to protecting the useful signals without interference. (3) The Generalized Singular Value Thresholding (GSVT) based low-rank sparse decomposition (LRSD) model was utilized to separate the RFI signals and the useful signals. Then, the useful signals were restored to the raw data. The simulation experiments and measured data experiments show that the proposed method can effectively mitigate RFI and protect the useful signals whether there are RFI with single source or multiple sources.

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21

Francos, J. M., and B. Friedlander. "Parameter estimation of 2-D random amplitude polynomial-phase signals." IEEE Transactions on Signal Processing 47, no. 7 (1999): 1795–810. http://dx.doi.org/10.1109/78.771030.

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22

Kaufman, H. J., and M. A. Sid-Ahmed. "Real-time 2-D homomorphic filter for broadcast TV signals." IEEE Transactions on Consumer Electronics 38, no. 2 (1992): 48–56. http://dx.doi.org/10.1109/30.142858.

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23

Reddy, G. R., P. Sathyanarayana, and M. N. S. Swamy. "CAS-CAS transform for 2-D signals: A few applications." Circuits Systems and Signal Processing 10, no. 2 (1991): 163–73. http://dx.doi.org/10.1007/bf01183769.

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24

Kim, S. P., and N. K. Bose. "Reconstruction of 2-D bandlimited discrete signals from nonuniform samples." IEE Proceedings F Radar and Signal Processing 137, no. 3 (1990): 197. http://dx.doi.org/10.1049/ip-f-2.1990.0030.

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25

Shimamura, Tetsuya, and Jouji Suzuki. "Spectral peak enhancement methods for 1-D and 2-D signals and their applications." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 76, no. 4 (1993): 106–15. http://dx.doi.org/10.1002/ecjc.4430760411.

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26

Murtianta, Budihardja, and Deddy Susilo. "PENGUAT KELAS D FREKUENSI TETAP ORDE 2." Jurnal Edukasi Elektro 6, no. 1 (2022): 24–31. http://dx.doi.org/10.21831/jee.v6i1.44196.

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ABSTRACT:The power amplifier determines the output power of the audio amplifier and in this part there will be heat dissipation which is proportional to the output power of the amplifier. To overcome the problem of the audio amplifier, a class D amplifier was designed. The amplifier designed in this paper is Power Amplifier Class D Fixed Frequency Second Order that uses a fixed frequency triangular signal generator and an order 2 low-pass filter. In this case, a power amplifier is designed for a subwoofer that has a frequency range of 20 Hz – 200 Hz because in the audio frequency range it requires relatively large power. The design of the power amplifier and its measurement using the Circuit Maker simulator. The amplifier can work to amplify signals with a maximum amplitude of 1 Vp and a frequency range of 20 Hz – 200 Hz. At a frequency of 20 Hz the shape of the signal is not as good as that of the 200 Hz frequency signal because it is far from the cut-off frequency of the low - pass filter, which is designed to be 250 Hz.ABSTRAK:Penguat daya menentukan besarnya daya keluaran penguat audio dan pada bagian ini akan terjadi disipasi panas yang sebanding dengan besar daya keluaran penguat. Untuk mengatasi permasalahan penguat audio tersebut dirancanglah penguat kelas D. Penguat yang di rancang pada tulisan ini adalah Penguat Kelas D Frekuensi Tetap Orde Dua yang menggunakan pembangkit sinyal segitiga frekuensi tetap dan tapis pelewat frekuensi rendah orde 2. Dalam hal ini dirancang penguat daya untuk subwoofer yang mempunyai jangkauan frekuensi 20 Hz – 200 Hz karena pada jangkauan frekuensi audio tersebut memerlukan daya relatif besar. Perancangan penguat daya dan pengukurannya menggunakan simulator Circuit Maker. Penguat dapat bekerja memperkuat sinyal dengan amplitudo maksimum 1 Vp dan jangkauan frekuensi 20 Hz – 200 Hz. Pada frekuensi 20 Hz bentuk sinyal tidak sebaik bentuk sinyal frekuensi 200 Hz karena jauh dari frekuensi penggal tapis pelewat frekuensi rendah yaitu dirancang 250 Hz.

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27

Xiao, Shungen, Ang Nie, Zexiong Zhang, Shulin Liu, Mengmeng Song, and Hongli Zhang. "Fault Diagnosis of a Reciprocating Compressor Air Valve Based on Deep Learning." Applied Sciences 10, no. 18 (2020): 6596. http://dx.doi.org/10.3390/app10186596.

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With the development of machine learning in recent years, the application of machine learning to machine fault diagnosis has become increasingly popular. Applying traditional feature extraction methods for complex systems will weaken the characterization capacity of features, which are not conducive to subsequent classification work. A reciprocating compressor is a complex system. In order to improve the fault diagnosis accuracy of complex systems, this paper does not use traditional fault diagnosis methods and applies deep convolutional neural networks (CNNs) to process this nonlinear and non-stationary fault signal. The valve fault data is obtained from the reciprocating compressor test bench of the Daqing Natural Gas Company. Firstly, the single-channel vibration signal is collected on the reciprocating compressor and the one-dimensional CNN (1-D CNN) is used for fault diagnosis and compared with the traditional model to verify the effectiveness of the 1-D CNN. Next, the collected eight channels signals (three channels of vibration signals, four channels of pressure signals, one channel key phase signal) are applied by 1-D CNN and 2-D CNN for fault diagnosis to verify the CNN that it is still suitable for multi-channel signal processing. Finally, further study on the influence of the input of different channel signal combinations on the model diagnosis accuracy is carried out. Experiments show that the seven-channel signal (three-channel vibration signal, four-channel pressure signal) with the key phase signal removed has the highest diagnostic accuracy in the 2-D CNN. Therefore, proper deletion of useless channels can not only speed up network operations but also improve diagnosis accuracy.

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28

Seliger, J., and R. Blinc. "2 D Methods in NQR Spectroscopy." Zeitschrift für Naturforschung A 47, no. 1-2 (1992): 333–41. http://dx.doi.org/10.1515/zna-1992-1-258.

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AbstractThe application of two-dimensional spectroscopy to nuclear quadrupole resonance (NQR) is reviewed with special emphasys on spin 3/2 nuclei. A new two-dimensional level crossing double resonance NQR nutation technique based on magnetic field cycling is described. This technique allows for a determination of both the electric quadrupole coupling constant and the asymmetry parameter for spin 3/2 nuclei in powdered samples even in cases where the quadrupolar signals are too weak to be observed directly. It works if the usual double resonance conditions are met, i.e. if the spin-lattice relaxation times are not too short if the quadrupolar nuclei are dipolarly coupled to "strong" nuclei. Variations of this techique can be also used for 2 D "exchange" NQR spectroscopy and NQR imaging.

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29

Hu, Jie, Wei Li, and Yong Jue Chen. "2-D DOA Estimation of Quasi-Stationary Signals via Tensor Modeling." Applied Mechanics and Materials 743 (March 2015): 458–62. http://dx.doi.org/10.4028/www.scientific.net/amm.743.458.

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A two-dimensional direction-of-arrival estimation of quasi-stationary signals via tensor modeling using an L-shape array is presented in this paper. This is a novel approach which is an extension of Khatri-Rao subspace approach, denoted by extended Khatri-Rao subspace approach. The proposed approach can work even when number of sensors is less than number of sources. To utilize the multilinear algebra, direction of arrival (DOA) is developed in the multidimensional sense. The effectiveness of the proposed method is verified through numerical examples.

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30

Li, J. S. J., and S. Luthi. "A real-time 2-D median based filter for video signals." IEEE Transactions on Consumer Electronics 39, no. 2 (1993): 115–21. http://dx.doi.org/10.1109/30.214816.

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31

Alexandre, E., A. Pena, and M. Sobreira. "On the Use of 2-D Coding Techniques for ECG Signals." IEEE Transactions on Information Technology in Biomedicine 10, no. 4 (2006): 809–11. http://dx.doi.org/10.1109/titb.2006.874926.

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32

Hao Lei, Zheng Chongxun, Huang Ying, and Cai Qun. "Detecting myocardial ischemia with 2-D spectrum analysis of VCG signals." IEEE Engineering in Medicine and Biology Magazine 16, no. 4 (1997): 33–40. http://dx.doi.org/10.1109/51.603646.

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33

Conner, Michael, and Yao Li. "Optical generation of the Wigner distribution of 2-D real signals." Applied Optics 24, no. 22 (1985): 3825. http://dx.doi.org/10.1364/ao.24.003825.

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34

Shenoy, Basty Ajay, and Chandra Sekhar Seelamantula. "Exact Phase Retrieval for a Class of 2-D Parametric Signals." IEEE Transactions on Signal Processing 63, no. 1 (2015): 90–103. http://dx.doi.org/10.1109/tsp.2014.2370935.

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35

Jin, Liang, Minli Yao, and Qinye Yin. "2-D direction finding of coherent signals VIA Temporo-Spatial processing." Journal of Electronics (China) 17, no. 1 (2000): 31–37. http://dx.doi.org/10.1007/s11767-000-0019-7.

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36

Abbas, Talib. "Arabic Speech Recognition Using Two Techniques Hybrid & 3D-Multiwavelet." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 1 (October 27, 2021): 116–31. http://dx.doi.org/10.55562/jrucs.v22i1.494.

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A key issue for implementing an accurate speech recognition system is the set of acoustic features extracted from speech signal. This paper presents two techniques for comparison. The first technique converts successfully the speech signal from (1-D) into two dimensional (2-D) forms. Next, the 2-D Multiwalidlet transform is applied to each 2-D signal. The second used transformation which is 3D-Multiwavelet (DMWT). For this transform set of speakers spoke the same word which arranged as slices of 2-D signals in acoustic space. These speakers represented the word as 3-D signal. The techniques apply the neural network as a classifier and dealing with text-dependent and text-independent speech recognition. The works are tested upon a database which consist of (28) speakers and uttered 7 Arabic words for each one. It was compared with first technique which gave the result (85.71%-100%), the second gave (71.43%-100%). It is clear that first give much better performance than the second one.

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37

Liu, Xuewei. "Ground roll supression using the Karhunen‐Loeve transform." GEOPHYSICS 64, no. 2 (1999): 564–66. http://dx.doi.org/10.1190/1.1444562.

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Ground roll is the main type of coherent noise in land seismic surveys, and is commonly much stronger in amplitude than the reflection signals. Standard methods for suppressing ground roll include 1-D high‐pass filtering and 2-D f-k filtering. High‐pass filtering is based on the low‐frequency nature of ground roll, but has the disadvantage that it also eliminates low‐frequency reflection signals which contribute to the character of reflection events and are very important in inversion for acoustic impedance. When the amplitude of the ground roll is much stronger than the reflection signals, f-k filters cause serious distortion of the signal.

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38

Abou-Loukh, Sadiq J., and Jaleel Sadoon Jameel. "Compression of an ECG Signal Using Mixed Transforms." Journal of Engineering 20, no. 06 (2023): 109–23. http://dx.doi.org/10.31026/j.eng.2014.06.08.

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Electrocardiogram (ECG) is an important physiological signal for cardiac disease diagnosis. With the increasing use of modern electrocardiogram monitoring devices that generate vast amount of data requiring huge storage capacity. In order to decrease storage costs or make ECG signals suitable and ready for transmission through common communication channels, the ECG datavolume must be reduced. So an effective data compression method is required. This paper presents an efficient technique for the compression of ECG signals. In this technique, different transforms have been used to compress the ECG signals. At first, a 1-D ECG data was segmented and aligned to a 2-D data array, then 2-D mixed transform was implemented to compress the ECG data in the 2-D form. The compression algorithms were implemented and tested using multiwavelet, wavelet and slantlet transforms to form the proposed method based on mixed transforms. Then vector quantization technique was employed to extract the mixed transform coefficients. Some selected records from MIT/BIH arrhythmia database were tested contrastively and the performance of theproposed methods was analyzed and evaluated using MATLAB package. Simulation results showed that the proposed methods gave a high compression ratio (CR) for the ECG signals comparing with other available methods. For example, the compression of one record (record 100) yielded CR of 24.4 associated with percent root mean square difference (PRD) of 2.56% was achieved.

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39

Su, Shu Jing, and Wen Qiang Zheng. "A Modified MUSIC Algorithm for DOA Estimation." Advanced Materials Research 658 (January 2013): 652–57. http://dx.doi.org/10.4028/www.scientific.net/amr.658.652.

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In this paper, a method of being modified 2-D DOA estimation is presented. By reconstructing covariance matrix of the received array data, the correlativity of the incident signals is recreased, and mis-division between signal subspace and noise subspace is controlled, therefore the number of estimated signals would be equal to the number of actual incident signals. This method has good performance not only for DOA estimation of the correlation signals, but for DOA estimation of the non-correlation signals. In addition the computational complexity will not increase obviously. The simulation tests verify the validity of the presented algorithm.

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40

Zeng, Hong-Cheng, Jie Chen, Peng-Bo Wang, Wei Yang, and Wei Liu. "2-D Coherent Integration Processing and Detecting of Aircrafts Using GNSS-Based Passive Radar." Remote Sensing 10, no. 7 (2018): 1164. http://dx.doi.org/10.3390/rs10071164.

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Long time coherent integration is a vital method for improving the detection ability of global navigation satellite system (GNSS)-based passive radar, because the GNSS signal is not radar-designed and its power level is very low. For aircraft detection, the large range cell migration (RCM) and Doppler frequency migration (DFM) will seriously affect the coherent processing of azimuth signals, and the traditional range match filter will also be mismatched due to the Doppler-intolerant characteristic of GNSS signals. Accordingly, the energy loss of 2-dimensional (2-D) coherent processing is inevitable in traditional methods. In this paper, a novel 2-D coherent integration processing and algorithm for aircraft target detection is proposed. For azimuth processing, a modified Radon Fourier Transform (RFT) with range-walk removal and Doppler rate estimation is performed. In respect to range compression, a modified matched filter with a shifting Doppler is applied. As a result, the signal will be accurately focused in the range-Doppler domain, and a sufficiently high SNR can be obtained for aircraft detection with a moving target detector. Numerical simulations demonstrate that the range-Doppler parameters of an aircraft target can be obtained, and the position and velocity of the aircraft can be estimated accurately by multiple observation geometries due to abundant GNSS resources. The experimental results also illustrate that the blind Doppler sidelobe is suppressed effectively and the proposed algorithm has a good performance even in the presence of Doppler ambiguity.

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41

Pal, Sujay, Yasuhide Hobara, Alexander Shvets, Peter Wilhelm Schnoor, Masashi Hayakawa, and Oleksandr Koloskov. "First Detection of Global Ionospheric Disturbances Associated with the Most Powerful Gamma Ray Burst GRB221009A." Atmosphere 14, no. 2 (2023): 217. http://dx.doi.org/10.3390/atmos14020217.

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We present the first report of global ionospheric disturbances due to the most powerful Gamma Ray Burst GRB221009A occurred on 9 October 2022. Very Low Frequency (VLF) and Low Frequency (LF) sub-ionospheric radio signals are used to diagnose the effect of the GRB on the lower ionosphere. Both daytime and nighttime effects are analyzed in VLF and LF bands. The magnitude of VLF signal perturbations varied with the propagation condition (day/night), path length, and frequency of the signal. The recovery times for the VLF/LF signals to get back to their pre-GRB levels varied from 2–60 min. Radio signals reflected from the E-region ionosphere for nighttime VLF signals and daytime LF signals showed greater effects compared to the daytime VLF signals reflected from the lower parts of the D-region.

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Abdala-Valencia, Hiam, Sergejs Berdnikovs та Joan Cook-Mills. "Vitamin E Isoforms Differentially Regulate Intercellular Adhesion Molecule-1 Activation of PKCα in Human Microvascular Endothelial Cells (173.25)". Journal of Immunology 188, № 1_Supplement (2012): 173.25. http://dx.doi.org/10.4049/jimmunol.188.supp.173.25.

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Abstract Leukocytes bind to ICAM-1 on endothelial cells during leukocyte transendothelial migration. ICAM-1 is reported to activate endothelial cell xanthine oxidase (XO), protein kinase C(PKC) and ERK1/2, but the PKC isoform and the pathway involving these signals is not known. PKCα can be directly regulated by vitamin E, but it is not known whether vitamin E regulates ICAM-1 activation of PKC. Therefore, we identified an ICAM-1 signaling pathway and determined whether these signals are regulated by the vitamin E isoforms d-α-tocopherol and d-γ-tocopherol. In primary cultures of TNFα-stimulated human microvascular endothelial cells, ICAM-1 crosslinking activated the PKC isoform PKCα but not PKCβ. ICAM-1-activated XO stimulated ERK1/2 activation that then induced activation of PKCα. ICAM-1 crosslinking did not induce oxidative activation of PKCα. D-α-tocopherol inhibited ICAM-1 activation of PKCα but not the upstream signal ERK1/2. The d-α-tocopherol inhibition of PKCα was ablated by the addition of d-γ-tocopherol. In summary, ICAM-1 activation of XO and ERK1/2 stimulates endothelial PKCα without oxidation of PKCα. ICAM-1 activation of PKCα is inhibited by d-α-tocopherol and this inhibition is ablated by d-γ-tocopherol. These data are consistent with PKCα antagonist and agonist functions of d-α-tocopherol and d-γ-tocopherol, respectively, during ICAM-1 signaling.

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CHEN, WEN-SHIUNG, and SHANG-YUAN YUAN. "SOME FRACTAL DIMENSION ESTIMATE ALGORITHMS AND THEIR APPLICATIONS TO ONE-DIMENSIONAL BIOMEDICAL SIGNALS." Biomedical Engineering: Applications, Basis and Communications 14, no. 03 (2002): 100–108. http://dx.doi.org/10.4015/s1016237202000152.

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Fractals can model many classes of time-series data. The fractal dimension is an important characteristic of fractals that contains information about their geometrical structure at multiple scales. The covering methods are a class of efficient approaches, e.g., box-counting (BC) method, to estimate the fractal dimension. In this paper, the differential box-counting (DBC) approach, originally for 2-D applications, is modified and applied to 1-D case. In addition, two algorithms, called 1-D shifting-DBC (SDBC-1D) and 1-D scanning-BC (SBC-1D), are also proposed for 1-D signal analysis. The fractal dimensions for 1-D biomedical pulse and ECG signals are calculated.

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Adiga, Umesh PS, Samantha JL Knight, and BB Chaudhuri. "CHARACTERIZATION AND AUTOMATIC COUNTING OF F.I.S.H. SIGNALS IN 3-D TISSUE IMAGES." Image Analysis & Stereology 20, no. 1 (2011): 41. http://dx.doi.org/10.5566/ias.v20.p41-52.

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The evaluation of malignancy-related features often helps to determine the prognoses for patients with carcinomas. One technique, which is becoming increasingly important for assessing such prognostic features is that of Fluorescence in situ Hybridization (FISH). By counting the number of FISH signals in a stack of 2- D images of a tumor (which together constitute the 3-D image volume), it is possible to determine whether there has been any loss or gain of the target DNA sequences and thereby evaluate the stage of the disease. However, visual counting of the FISH signals in this way is a tedious, fatiguing and time-consuming task. Therefore, we have developed an automated system for the quantitative evaluation of FISH signals. We present and discuss the implementation of an image processing module that segments, characterizes and counts the FISH signals in 3-D images of thick prostate tumor tissue specimens. Possible errors in the automatic counting of signals are listed and ways to circumvent these errors are described. We define a feature vector for a FISH signal and describe how we have used the weighted feature vector to segment specific signals from noise artifacts. In addition, we present a method, which allows overlapping FISH signals to be distinguished by fitting a local Gaussian model around the intensity profile and studying the feature vector of each model. Our complete image processing module overcomes the problems of manual counting of FISH signals in 3-D images of tumor specimens, thereby providing improved diagnostic and prognostic capability in qualitative diagnostic pathology.

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Matsuura, Tsutomu, Amirul Faiz, and Kouji Kiryu. "Separation and Reproduction of Mixed Images Using 2-D Complex Wavelet Transform." Applied Mechanics and Materials 36 (October 2010): 466–75. http://dx.doi.org/10.4028/www.scientific.net/amm.36.466.

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The differences method between 1-D wavelet transform and 2-D wavelet transform in image processing is discussed. Both proposed method uses the quotient of complex valued time-frequency information of observed signals to detect the number of sources. No less number of observed signals than the detected number of sources is needed to separate sources. The assumption on sources is quite general independence in the time-frequency plane, which is different from that of independent component analysis. Using the same given Algorithm and parameters for both method, the result on separated images are compared.

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Ullah, Amin, Syed Muhammad Anwar, Muhammad Bilal, and Raja Majid Mehmood. "Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation." Remote Sensing 12, no. 10 (2020): 1685. http://dx.doi.org/10.3390/rs12101685.

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The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture the heart’s rhythmic irregularities, commonly known as arrhythmias. A careful study of ECG signals is crucial for precise diagnoses of patients’ acute and chronic heart conditions. In this study, we propose a two-dimensional (2-D) convolutional neural network (CNN) model for the classification of ECG signals into eight classes; namely, normal beat, premature ventricular contraction beat, paced beat, right bundle branch block beat, left bundle branch block beat, atrial premature contraction beat, ventricular flutter wave beat, and ventricular escape beat. The one-dimensional ECG time series signals are transformed into 2-D spectrograms through short-time Fourier transform. The 2-D CNN model consisting of four convolutional layers and four pooling layers is designed for extracting robust features from the input spectrograms. Our proposed methodology is evaluated on a publicly available MIT-BIH arrhythmia dataset. We achieved a state-of-the-art average classification accuracy of 99.11%, which is better than those of recently reported results in classifying similar types of arrhythmias. The performance is significant in other indices as well, including sensitivity and specificity, which indicates the success of the proposed method.

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Gao, Yongxin, Dongdong Wang, Jian Wen, Hengshan Hu, Xiaofei Chen, and Cheng Yao. "Electromagnetic responses to an earthquake source due to the motional induction effect in a 2-D layered model." Geophysical Journal International 219, no. 1 (2019): 563–93. http://dx.doi.org/10.1093/gji/ggz303.

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Summary Movement of the conductive earth medium in the ambient geomagnetic field can generate an electromotive force and a motional induction current, which further cause the disturbances of the electromagnetic (EM) fields. Such a mechanoelectric coupling is known as the motional induction (MI) effect and has been proposed to be a possible mechanism for the generation of the observed EM signals during earthquakes. In this paper, we study the EM responses to an earthquake source due to such a MI effect in a 2-D horizontally layered model. First we transform the governing equations that couple the elastodynamic equations and Maxwell equations into a set of first-order ordinary depth-dependent differential equations. Then we solve the seismic and EM responses to a moment tensor source. Finally, we transform the 2-D seismic and EM responses to 3-D responses using a simple amplitude correction method. We conduct several numerical examples to investigate the properties of the EM signals generated by the earthquake source. The results show that two types of EM signals can be observed. The first one is the coseismic electric/magnetic field that accompanies the seismic P and S waves as well as the Rayleigh wave. The second one is the early EM signal which arrives before the P wave. The numerical results show that the EM signals change with the inclination angle of the geomagnetic field, the azimuth angle between the wave propagation plane and the geomagnetic vertical plane, and the medium conductivity. Increase in the conductivity can enhance the coseismic electric and magnetic signals. Our simulation also shows that an EM wave can be generated by a seismic wave at the interface separating two different media. The radiation pattern of the interface EM wave generated by a P wave is similar to that of a horizontal electric dipole located on the interface.

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Prasuna, K., and M. Padmaja. "Statistical Analysis of 2-D signals using Power allocation over wireless channels." Procedia Engineering 30 (2012): 922–29. http://dx.doi.org/10.1016/j.proeng.2012.01.946.

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Maravic, I., and M. Vetterli. "Exact Sampling Results for Some Classes of Parametric Nonbandlimited 2-D Signals." IEEE Transactions on Signal Processing 52, no. 1 (2004): 175–89. http://dx.doi.org/10.1109/tsp.2003.819984.

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Hahn, S. L., and K. M. Snopek. "Wigner distributions and ambiguity functions of 2-D quaternionic and monogenic signals." IEEE Transactions on Signal Processing 53, no. 8 (2005): 3111–28. http://dx.doi.org/10.1109/tsp.2005.851134.

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