Relevant bibliographies by topics / Multicomponent phase signals

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Multicomponent phase signals'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 January 2023

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Journal articles on the topic "Multicomponent phase signals"

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Tang, Peng Fei, Bin Yuan, Qian Qiang Lin, and Zeng Ping Chen. "Parameter Estimation of Multicomponent Cubic Phase Signals." Applied Mechanics and Materials 380-384 (August 2013): 3726–29. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3726.

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This paper presents an algorithm for estimating the parameters of multicomponent cubic phase signals. This algorithm combines the product generalized cubic phase function (PGCPF) and the product cubic phase function (PCPF) which are used to estimate the cubic phase coefficient and chirp rate of the cubic phase signal, respectively. This algorithm starts by estimating the parameters of the signal component with the strongest amplitude. Then removing the signal component whose parameters have been estimated, it proceeds to estimate the next signal component, and so on, until all of the signal co
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Pham, Duc Son, and Abdelhak M. Zoubir. "Analysis of Multicomponent Polynomial Phase Signals." IEEE Transactions on Signal Processing 55, no. 1 (2007): 56–65. http://dx.doi.org/10.1109/tsp.2006.882085.

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Friedlander, B., and J. M. Francos. "Estimation of amplitude and phase parameters of multicomponent signals." IEEE Transactions on Signal Processing 43, no. 4 (1995): 917–26. http://dx.doi.org/10.1109/78.376844.

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Ikram, Muhammad Z., and G. Tong Zhou. "Estimation of multicomponent polynomial phase signals of mixed orders." Signal Processing 81, no. 11 (2001): 2293–308. http://dx.doi.org/10.1016/s0165-1684(01)00095-0.

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Duc Son Pham and A. M. Zoubir. "Estimation of Multicomponent Polynomial Phase Signals With Missing Observations." IEEE Transactions on Signal Processing 56, no. 4 (2008): 1710–15. http://dx.doi.org/10.1109/tsp.2007.909345.

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Wang, Yong, and Yi-cheng Jiang. "Generalized time–frequency distributions for multicomponent polynomial phase signals." Signal Processing 88, no. 4 (2008): 984–1001. http://dx.doi.org/10.1016/j.sigpro.2007.10.016.

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Wang, Pu, and Jianyu Yang. "Multicomponent chirp signals analysis using product cubic phase function." Digital Signal Processing 16, no. 6 (2006): 654–69. http://dx.doi.org/10.1016/j.dsp.2006.09.002.

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Liu, Jing-Liang, Jin-Yang Zheng, Xiao-Jun Wei, Fei-Yu Liao, and Yong-Peng Luo. "A new instantaneous frequency extraction method for nonstationary response signals in civil engineering structures." Journal of Low Frequency Noise, Vibration and Active Control 37, no. 4 (2018): 834–48. http://dx.doi.org/10.1177/1461348418790534.

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Civil engineering structures in essence belong to time-varying and nonlinear structures and the resultant dynamic responses are usually nonstationary signals. A new method is proposed to extract instantaneous frequency of such nonstationary signals. The new method combines the extended analytical mode decomposition, normalization scheme, and improved arccosine function algorithm. In this method, a multicomponent response signal is first decomposed into several mono-components signals by the extended analytical mode decomposition theorem, and then the extracted mono-components are demodulated i
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Bratchenko, H. D., М. O. Koptielov, H. H. Smahliuk, and M. A. Martynov. "ACCURACY ESTIMATION OF MEASURING THE INSTANTANEOUS FREQUENCIES AND PHASES OF COMPONENTS OF THE MULTICOMPONENT NON-STATIONARY SIGNAL." Key title: Zbìrnik naukovih pracʹ Odesʹkoï deržavnoï akademìï tehnìčnogo regulûvannâ ta âkostì, no. 2(19) (2021): 48–62. http://dx.doi.org/10.32684/2412-5288-2021-2-19-48-62.

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Measurements of instantaneous frequencies and phases of non-stationary components of the multicomponent signals are actual in processing medical, radar, sonar, seismic, vibration, and speech signals. When we measure the parameters of multi-component non-stationary signals, it is a need to measure the instantaneous frequency and current phase of several non-stationary frequency-modulated signal components. In this article, estimates of the measurement accuracy of the specified parameters of the non-stationary signal components were obtained using the method of simulation modeling. Measurement m
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OU, GuoJian, ShiZhong YANG, JianXun DENG, QingPing JIANG, and TianQi ZHANG. "A Refined Estimator of Multicomponent Third-Order Polynomial Phase Signals." IEICE Transactions on Communications E99.B, no. 1 (2016): 143–51. http://dx.doi.org/10.1587/transcom.2015ebp3131.

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Dissertations / Theses on the topic "Multicomponent phase signals"

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Farquharson, Maree Louise. "Estimating the parameters of polynomial phase signals." Thesis, Queensland University of Technology, 2006. https://eprints.qut.edu.au/16312/1/Maree_Farquharson_Thesis.pdf.

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Nonstationary signals are common in many environments such as radar, sonar, bioengineering and power systems. The nonstationary nature of the signals found in these environments means that classicalspectralanalysis techniques are notappropriate for estimating the parameters of these signals. Therefore it is important to develop techniques that can accommodate nonstationary signals. This thesis seeks to achieve this by firstly, modelling each component of the signal as having a polynomial phase and by secondly, developing techniques for estimating the parameters of these components. Several
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Farquharson, Maree Louise. "Estimating the parameters of polynomial phase signals." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16312/.

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Nonstationary signals are common in many environments such as radar, sonar, bioengineering and power systems. The nonstationary nature of the signals found in these environments means that classicalspectralanalysis techniques are notappropriate for estimating the parameters of these signals. Therefore it is important to develop techniques that can accommodate nonstationary signals. This thesis seeks to achieve this by firstly, modelling each component of the signal as having a polynomial phase and by secondly, developing techniques for estimating the parameters of these components. Several app
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Hussain, Zahir M. "Adaptive instantaneous frequency estimation: Techniques and algorithms." Thesis, Queensland University of Technology, 2002. https://eprints.qut.edu.au/36137/7/36137_Digitised%20Thesis.pdf.

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This thesis deals with the problem of the instantaneous frequency (IF) estimation of sinusoidal signals. This topic plays significant role in signal processing and communications. Depending on the type of the signal, two major approaches are considered. For IF estimation of single-tone or digitally-modulated sinusoidal signals (like frequency shift keying signals) the approach of digital phase-locked loops (DPLLs) is considered, and this is Part-I of this thesis. For FM signals the approach of time-frequency analysis is considered, and this is Part-II of the thesis. In part-I we have uti
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Björk, Marcus. "Contributions to Signal Processing for MRI." Doctoral thesis, Uppsala universitet, Avdelningen för systemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-246537.

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Magnetic Resonance Imaging (MRI) is an important diagnostic tool for imaging soft tissue without the use of ionizing radiation. Moreover, through advanced signal processing, MRI can provide more than just anatomical information, such as estimates of tissue-specific physical properties. Signal processing lies at the very core of the MRI process, which involves input design, information encoding, image reconstruction, and advanced filtering. Based on signal modeling and estimation, it is possible to further improve the images, reduce artifacts, mitigate noise, and obtain quantitative tissue info
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Books on the topic "Multicomponent phase signals"

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Kulkarni, Rishikesh. Single and Multicomponent Digital Optical Signal Analysis: Estimation of Phase and Its Derivatives. Institute of Physics Publishing, 2017.

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Book chapters on the topic "Multicomponent phase signals"

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Kitagawa, Jiro, Naoki Ishizu, and Shusuke Hamamoto. "Materials Research on High-Entropy Alloy Superconductors." In Advances in High-Entropy Alloys - Materials Research, Exotic Properties and Applications [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.99693.

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The first purpose of this chapter is materials research on face-centered-cubic (fcc) high-entropy alloy (HEA) superconductors, which have not yet been reported. We have investigated several Nb-containing multicomponent alloys. Although we succeeded in obtaining Nb-containing samples with the dominant fcc phases, no superconducting signals appeared in these samples down to 3 K. The microstructure analyses revealed that all samples were multi-phase, but the existence of several new Nb-containing HEA phases was confirmed in them. The second purpose is the report of materials research on the Mn5Si3-type HEA superconductors. This hexagonal structure offers various intermetallic compounds, which often undergo a superconducting state. The Mn5Si3-type HEA is classified into the multisite HEA, which possesses the high degree of freedom in the materials design and is good platform for studying exotic HEA superconductors. We have successfully found a single-phase Mn5Si3-type HEA, which, however, does not show a superconducting property down to 3 K. The attempt of controlling the valence electron count was not successful.
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Rastogi, Pramod. "Phase estimation: multicomponent spatial fringe analysis." In Single and Multicomponent Digital Optical Signal Analysis Estimation of phase and its derivatives. IOP Publishing, 2017. http://dx.doi.org/10.1088/978-0-7503-1469-5ch4.

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Rastogi, Pramod. "Signal separation techniques: multicomponent spatial fringe analysis." In Single and Multicomponent Digital Optical Signal Analysis Estimation of phase and its derivatives. IOP Publishing, 2017. http://dx.doi.org/10.1088/978-0-7503-1469-5ch7.

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Kulkarni, Rishikesh, and Pramod Rastogi. "Phase estimation: spatial fringe analysis." In Single and Multicomponent Digital Optical Signal Analysis Estimation of phase and its derivatives. IOP Publishing, 2017. http://dx.doi.org/10.1088/978-0-7503-1469-5ch2.

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Kulkarni, Rishikesh, and Pramod Rastogi. "Fringe denoising and phase unwrapping." In Single and Multicomponent Digital Optical Signal Analysis Estimation of phase and its derivatives. IOP Publishing, 2017. http://dx.doi.org/10.1088/978-0-7503-1469-5ch3.

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Rastogi, Pramod. "Phase estimation: temporal fringe analysis." In Single and Multicomponent Digital Optical Signal Analysis Estimation of phase and its derivatives. IOP Publishing, 2017. http://dx.doi.org/10.1088/978-0-7503-1469-5ch8.

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Rastogi, Pramod. "Phase derivative estimation: spatial fringe analysis." In Single and Multicomponent Digital Optical Signal Analysis Estimation of phase and its derivatives. IOP Publishing, 2017. http://dx.doi.org/10.1088/978-0-7503-1469-5ch5.

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Rastogi, Pramod. "Simultaneous estimation of unwrapped phase and its derivatives." In Single and Multicomponent Digital Optical Signal Analysis Estimation of phase and its derivatives. IOP Publishing, 2017. http://dx.doi.org/10.1088/978-0-7503-1469-5ch6.

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Kulkarni, Rishikesh, and Pramod Rastogi. "Introduction." In Single and Multicomponent Digital Optical Signal Analysis Estimation of phase and its derivatives. IOP Publishing, 2017. http://dx.doi.org/10.1088/978-0-7503-1469-5ch1.

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Conference papers on the topic "Multicomponent phase signals"

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Djukanovic, Slobodan, Marko Simeunovic, and Igor Djurovic. "Refinement in the estimation of multicomponent polynomial-phase signals." In ICASSP 2012 - 2012 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2012. http://dx.doi.org/10.1109/icassp.2012.6288784.

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Han-ling, Zhang, and Liu Qing-yun. "Estimation of instantaneous frequency rate for multicomponent polynominal phase signals." In 2006 8th international Conference on Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/icosp.2006.344448.

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Pejakovic, Tamara, Milos Orovic, and Irena Orovic. "A comparison of CS reconstruction algorithms for multicomponent nonlinear phase signals." In 2015 4th Mediterranean Conference on Embedded Computing (MECO). IEEE, 2015. http://dx.doi.org/10.1109/meco.2015.7181898.

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Tang, Pengfei, Bin Yuan, Qianqiang Lin, and Zengping Chen. "An Efficient Algorithm for Estimating the Parameters of Multicomponent Cubic Phase Signals." In 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013). Atlantis Press, 2013. http://dx.doi.org/10.2991/iccsee.2013.457.

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Pham, Duc Son, Yee Hong Leung, Kok Lay Teo, and Abdelhak Zoubir. "An Optimisation Approach to Robust Estimation of Multicomponent Polynomial Phase Signals in Non-Gaussian Noise." In APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/apccas.2006.342150.

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Ou, Guojian, and Zhongli Liu. "A modified CPF algorithm for estimating the parameters of multicomponent third-order polynomial phase signals." In 2017 IEEE 17th International Conference on Communication Technology (ICCT). IEEE, 2017. http://dx.doi.org/10.1109/icct.2017.8359657.

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Zhang, Kunlei, Shuxun Wang, and Fan Cao. "Product Cubic Phase Function Algorithm for Estimating the Instantaneous Frequency Rate of Multicomponent Two-Dimensional Chirp Signals." In 2008 Congress on Image and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/cisp.2008.352.

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You might also be interested in the extended bibliographies on the topic 'Multicomponent phase signals' for particular source types:
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