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Journal articles on the topic 'Spectrum analysis'

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1

Cokelaer, Thomas, and Juergen Hasch. "'Spectrum': Spectral Analysis in Python." Journal of Open Source Software 2, no. 18 (October 27, 2017): 348. http://dx.doi.org/10.21105/joss.00348.

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2

Harrar, Khaled, and Mohamed Khider. "Texture Analysis Using Multifractal Spectrum." International Journal of Modeling and Optimization 4, no. 4 (August 2014): 336–41. http://dx.doi.org/10.7763/ijmo.2014.v4.396.

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3

Charleston, M. A. "Spectrum: spectral analysis of phylogenetic data." Bioinformatics 14, no. 1 (February 1, 1998): 98–99. http://dx.doi.org/10.1093/bioinformatics/14.1.98.

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4

Bujunuru, Anitha, and Srinivasulu Tadisetty. "Performance Analysis of Spectrum Sensing Techniques." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (September 25, 2019): 355–61. http://dx.doi.org/10.5373/jardcs/v11/20192579.

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5

Dobigeon, Nicolas, and Nathalie Brun. "Spectral mixture analysis of EELS spectrum-images." Ultramicroscopy 120 (September 2012): 25–34. http://dx.doi.org/10.1016/j.ultramic.2012.05.006.

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6

Pedersen, Steen. "Spectral Sets Whose Spectrum Is a Lattice with a Base." Journal of Functional Analysis 141, no. 2 (November 1996): 496–509. http://dx.doi.org/10.1006/jfan.1996.0139.

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7

Amouch, M., M. Benharrat, and B. Messirdi. "RETRACTED: Spectral mapping theorem for generalized Kato spectrum." Journal of Mathematical Analysis and Applications 423, no. 1 (March 2015): 1–9. http://dx.doi.org/10.1016/j.jmaa.2014.09.043.

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8

Retcofsky, H. L. "Spectrum Analysis Discoverer?" Journal of Chemical Education 80, no. 9 (September 2003): 1003. http://dx.doi.org/10.1021/ed080p1003.1.

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9

Patil, S. P., N. R. Phadnis, and S. A. Patil. "Power Spectrum Analysis." IETE Technical Review 17, no. 3 (May 2000): 119–21. http://dx.doi.org/10.1080/02564602.2000.11416892.

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10

Wu, T., P.-Y. Chen, C.-H. Chen, and C.-L. Wang. "Doppler spectrum analysis." Journal of Bone and Joint Surgery. British volume 94-B, no. 3 (March 2012): 344–47. http://dx.doi.org/10.1302/0301-620x.94b3.27122.

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11

Fernández-Ramírez, C., L. Muñoz, A. Relaño, and J. Retamosa. "Spectral-statistics analysis of the light meson spectrum." EPJ Web of Conferences 37 (2012): 04001. http://dx.doi.org/10.1051/epjconf/20123704001.

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12

Wang, Xiaodong, Jialun Dai, Yafei Zhu, Haiyong Zheng, and Xiaoyan Qiao. "Spectral saliency via automatic adaptive amplitude spectrum analysis." Journal of Electronic Imaging 25, no. 2 (April 12, 2016): 023020. http://dx.doi.org/10.1117/1.jei.25.2.023020.

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13

HEGGE, BRUCE J., and GERHARD MASSELINK. "SPECTRAL ANALYSIS OF GEOMORPHIC TIME SERIES: AUTO-SPECTRUM." Earth Surface Processes and Landforms 21, no. 11 (November 1996): 1021–40. http://dx.doi.org/10.1002/(sici)1096-9837(199611)21:11<1021::aid-esp703>3.0.co;2-d.

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14

Baskakov, A. G., and I. A. Krishtal. "Spectral analysis of operators with the two-point Bohr spectrum." Journal of Mathematical Analysis and Applications 308, no. 2 (August 2005): 420–39. http://dx.doi.org/10.1016/j.jmaa.2004.11.006.

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15

Zhang, Yan Li. "Acoustic Signals Analysis Based on Empirical Mode Decomposition and Spectrum Analysis Technique." Applied Mechanics and Materials 40-41 (November 2010): 91–95. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.91.

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A method to analyze the acoustic signals collected in fully-mechanized caving face is presented in this paper. Through analyzing the marginal spectrum and frequency spectrum of intrinsic mode functions obtained by empirical mode decomposition, acoustic signals’ frequency and amplitude characteristics are gotten, that is, high frequency signals about 1000Hz ~2800Hz are produced when the top coal is combined with gangue. Furthermore, the acoustic signals’ instantaneous energy spectrums in the frequency range of 1000Hz ~2800Hz can be used to identify the coal-rock interface.
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16

Zhang, Lian Shun, and Ai Juan Shi. "Classification of Biological Spectrum Based on Principal Component Cluster Analysis." Advanced Materials Research 605-607 (December 2012): 2245–48. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.2245.

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Spectrums of 17 biological tissue phantoms were measured using the fiber-optic spectrometer. Then, the spectrum was preprocessed by multiplicative scatter correction method to devoice the spectrum. Afterwards the features of the spectrum were extracted via principal component analysis. Ultimately, we applied cluster analysis for the spectral features. The results showed that the accumulated credibility of the first 12 spectral principal components was 99.86% for the spectrum after preprocessing; indicating that this spectrum feature extraction might be done in the case of losing no key information. And the results showed that the 17 biological tissue phantoms can be divided into four main categories according their optical features.
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17

Tikhonov, A. S. "Spectral Components of Operators with Spectrum on a Curve." Functional Analysis and Its Applications 37, no. 2 (April 2003): 155–56. http://dx.doi.org/10.1023/a:1024465208838.

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18

Vallev, Anvar. "COMBINED VIBRATION AND STRAIN GAUGE ANALYSIS FOR DIAGNOSTICS OF INDUSTRIAL MACHINES." VOLUME 39, VOLUME 39 (2021): 38. http://dx.doi.org/10.36336/akustika20213938.

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The Paper is devoted to combined vibration and strain gauge analysis for diagnostics of industrial machines. It is suggested to use strain gauge spectrum analysis. For studying it an experimental installation is designed and created. This installation allows getting signal from strain gauge sensors with maximum frequency 12.87 kHz. According to experimental study application of strain gauge spectrum analysis can provide almost the same information as vibration spectrum analysis. Combination of these two spectrums can give more useful information. Particularly it can be used for filtering noise. In the experimental study spectrums were significantly cleared without any instrumental and digital filters, it was done only by analysis of combination of the spectrums. This study can provide more reliable diagnostics of industrial machines.
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19

Yuan, Jiangtao, and Caihong Wang. "Spectral mapping theorems for Weyl spectrum and isolated spectral points." Operators and Matrices, no. 2 (2019): 349–61. http://dx.doi.org/10.7153/oam-2019-13-25.

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20

Li, Chong, Shujie Li, Zhaoli Liu, and Jianzhong Pan. "On the Fucík spectrum." Journal of Differential Equations 244, no. 10 (May 2008): 2498–528. http://dx.doi.org/10.1016/j.jde.2008.02.021.

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21

Yang, Rongwei. "Functional spectrum of contractions." Journal of Functional Analysis 250, no. 1 (September 2007): 68–85. http://dx.doi.org/10.1016/j.jfa.2007.05.015.

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22

Davies, E. B. "Decomposing the essential spectrum." Journal of Functional Analysis 257, no. 2 (July 2009): 506–36. http://dx.doi.org/10.1016/j.jfa.2009.01.031.

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23

Alaminos, J., J. Extremera, and A. R. Villena. "Approximately spectrum-preserving maps." Journal of Functional Analysis 261, no. 1 (July 2011): 233–66. http://dx.doi.org/10.1016/j.jfa.2011.02.020.

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24

Lee, UkJae, Jun Woo Bae, and Hee Reyoung Kim. "Multiple beta spectrum analysis based on spectrum fitting." Journal of Radioanalytical and Nuclear Chemistry 314, no. 2 (August 19, 2017): 617–22. http://dx.doi.org/10.1007/s10967-017-5409-5.

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25

Andrejev, V. G., Ngoc L. Tran, and Tien P. Nguyen. "Parametric Spectral Analysis of Noisy Signals with Unimodal Spectrum." Radioelectronics and Communications Systems 62, no. 1 (January 2019): 34–41. http://dx.doi.org/10.3103/s0735272719010059.

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26

Andreyev, V. G., and H. L. Tran. "PARAMETRIC SPECTRAL ANALYSIS OF UNIMODAL SPECTRUM FOR NOISY SIGNALS." Vestnik of Ryazan State Radio Engineering University 59, no. 3 (2016): 3–8. http://dx.doi.org/10.21667/1995-4565-2016-57-3-3-8.

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27

Du Shan, 杜杉, 张国玉 Zhang Guoyu, 韩欣欣 Han Xinxin, 徐阳 Xu Yang, 迟明波 Chi Mingbo, and 吴一辉 Wu Yihui. "Design of Wide-Spectrum High-Resolution Spectral Analysis System." Laser & Optoelectronics Progress 56, no. 8 (2019): 083003. http://dx.doi.org/10.3788/lop56.083003.

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28

Katz‐Stone, D. M., and L. Rudnick. "A Spectral Analysis of Two Compact Steep‐Spectrum Sources." Astrophysical Journal 479, no. 1 (April 10, 1997): 258–67. http://dx.doi.org/10.1086/303882.

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29

Schulz, Michael, and Karl Stattegger. "Spectrum: spectral analysis of unevenly spaced paleoclimatic time series." Computers & Geosciences 23, no. 9 (November 1997): 929–45. http://dx.doi.org/10.1016/s0098-3004(97)00087-3.

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30

Hou, Jin-Chuan, and Xiu-Ling Zhang. "On the Weyl Spectrum: Spectral Mapping Theorem and Weyl's Theorem." Journal of Mathematical Analysis and Applications 220, no. 2 (April 1998): 760–68. http://dx.doi.org/10.1006/jmaa.1997.5897.

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31

Qiu, Zhigang, Weiwei Zhu, Jun Du, and Guojian Feng. "Spectral Analysis Method of Seismic Waves: Time-Frequency Response Spectrum." International Journal for Housing Science and Its Applications 45, no. 4 (December 30, 2024): 98–106. https://doi.org/10.70517/ijhsa4549.

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The commonly used spectrum analysis methods are summarized and their problems are analyzed. In this paper, the time-domain response spectrum is first analyzed and the frequency-domain normalized spectrum is given. The normalized time-frequency response spectra are calculated and compared by four typical ground vibration waveforms. This project will use the standardized time-frequency response spectrum analysis method to analyze the susceptibility of impact ground shaking and ground motions containing rich high-frequency components to structural damage under the action of strong earthquakes. The results show that the method can better reflect the ground shaking response characteristics and the damage mechanism of the structure. The model also reflects the role of seismic calendar time on the cumulative damage of buildings.
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32

Malm, H. L., H. J. Dixon, L. D. Cass, and J. J. Lipsett. "Real time spectrum analysis." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 242, no. 3 (January 1986): 501–6. http://dx.doi.org/10.1016/0168-9002(86)90454-7.

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33

Holmström, Lasse, and Ilkka Launonen. "Posterior singular spectrum analysis." Statistical Analysis and Data Mining: The ASA Data Science Journal 6, no. 5 (July 8, 2013): 387–402. http://dx.doi.org/10.1002/sam.11195.

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34

Moskvina, V., and K. M. Schmidt. "Approximate Projectors in Singular Spectrum Analysis." SIAM Journal on Matrix Analysis and Applications 24, no. 4 (January 2003): 932–42. http://dx.doi.org/10.1137/s0895479801398967.

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35

KUMAR C M, PUNEETH, and Dr MOHAMED HANEEF. "Response Spectrum and Impulse Excitation Analysis of DMAP Container." Indian Journal of Applied Research 4, no. 7 (October 1, 2011): 183–84. http://dx.doi.org/10.15373/2249555x/july2014/55.

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36

Yongli Zhao, Yongli Zhao, and Jie Zhang Jie Zhang. "Blocking probability analysis model for flexible spectrum optical networks." Chinese Optics Letters 12, no. 7 (2014): 070601–70606. http://dx.doi.org/10.3788/col201412.070601.

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37

Čejka, J. "Vandenbrandeite, CuUO2(OH)4: Thermal analysis and infrared spectrum." Neues Jahrbuch für Mineralogie - Monatshefte 1994, no. 3 (March 15, 1994): 112–20. http://dx.doi.org/10.1127/njmm/1994/1994/112.

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38

McDonald, Patrick, and Robert Meyers. "Dirichlet spectrum and heat content." Journal of Functional Analysis 200, no. 1 (May 2003): 150–59. http://dx.doi.org/10.1016/s0022-1236(02)00076-9.

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39

Cade, Patrick, and Rongwei Yang. "Projective spectrum and cyclic cohomology." Journal of Functional Analysis 265, no. 9 (November 2013): 1916–33. http://dx.doi.org/10.1016/j.jfa.2013.07.010.

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40

Romanov, Roman, and Harald Woracek. "Canonical systems with discrete spectrum." Journal of Functional Analysis 278, no. 4 (March 2020): 108318. http://dx.doi.org/10.1016/j.jfa.2019.108318.

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41

Donnelly, Harold. "Essential spectrum and heat kernel." Journal of Functional Analysis 75, no. 2 (December 1987): 362–81. http://dx.doi.org/10.1016/0022-1236(87)90101-7.

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42

Courtois, G. "Spectrum of Manifolds with Holes." Journal of Functional Analysis 134, no. 1 (November 1995): 194–221. http://dx.doi.org/10.1006/jfan.1995.1142.

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43

Bunke, Ulrich, and Martin Olbrich. "The Spectrum of Kleinian Manifolds." Journal of Functional Analysis 172, no. 1 (April 2000): 76–164. http://dx.doi.org/10.1006/jfan.1999.3494.

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44

Bayart, Frédéric, and Sophie Grivaux. "Hypercyclicity and unimodular point spectrum." Journal of Functional Analysis 226, no. 2 (September 2005): 281–300. http://dx.doi.org/10.1016/j.jfa.2005.06.001.

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45

Sun, Wen Xiang. "Characteristic Spectrum for Differential Systems." Journal of Differential Equations 147, no. 1 (July 1998): 184–94. http://dx.doi.org/10.1006/jdeq.1998.3434.

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46

Kuzma, B. "Additive spectrum compressors." Journal of Mathematical Analysis and Applications 304, no. 1 (April 2005): 13–21. http://dx.doi.org/10.1016/j.jmaa.2004.09.004.

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47

Dolinar, Gregor, Bojan Kuzma, Janko Marovt, and Edward Poon. "Spectrum preservers revisited." Journal of Mathematical Analysis and Applications 489, no. 1 (September 2020): 124144. http://dx.doi.org/10.1016/j.jmaa.2020.124144.

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48

Sánchez-Perales, S., and S. V. Djordjević. "Continuity of spectrum and approximate point spectrum on operator matrices." Journal of Mathematical Analysis and Applications 378, no. 1 (June 2011): 289–94. http://dx.doi.org/10.1016/j.jmaa.2011.01.062.

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49

Kim, Chang-Joo, Young-Heung Kang, Kyung-Moon Kye, Young Soo Kim, Duk-Kyu Park, Seokji Park, Jung-Kee Bae, and Hyun-Bo Yoon. "Analysis of Spectrum Sharing Policy and Spectrum Usage Rights." Journal of Korean Institute of Electromagnetic Engineering and Science 24, no. 8 (August 31, 2013): 805–19. http://dx.doi.org/10.5515/kjkiees.2013.24.8.805.

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50

Cueva, P., R. Hovden, and D. Muller. "Cornell Spectrum Imager: Open Source Spectrum Analysis with ImageJ." Microscopy and Microanalysis 17, S2 (July 2011): 792–93. http://dx.doi.org/10.1017/s1431927611004831.

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