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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

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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

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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 de

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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 vertica

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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-

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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-prote

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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 requ

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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

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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 rel

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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 ap

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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-

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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 E

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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 te

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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 inevi

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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 s

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42

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-stimulat

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43

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 fracta

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44

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 tedio

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45

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 c

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46

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 b

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47

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 t

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48

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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49

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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50

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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