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Journal articles on the topic 'Modélisation du signal'

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Author: Grafiati

Published: 22 April 2023

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1

Glockner, Ste´phane, Jean-Paul Caltagirone, and Paul Morel. "Mode´lisation d'e´coulements dans des espaces urbains." International Journal of Thermal Sciences 38, no. 8 (September 1999): 703–11. http://dx.doi.org/10.1016/s1290-0729(99)80063-5.

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2

Borghi,, R., M. Champion,, JL Torero,, and A. Atreya,. "Mode´lisation et The´orie des Flammes. Modeling and Theory of Flames. (French)." Applied Mechanics Reviews 54, no. 5 (September 1, 2001): B93—B94. http://dx.doi.org/10.1115/1.1399681.

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3

Mei, Fei, Zhihong Man, and Xinghuo Yu. "Sliding mode control signal analysis." IFAC Proceedings Volumes 32, no. 2 (July 1999): 4118–22. http://dx.doi.org/10.1016/s1474-6670(17)56702-6.

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4

Männama, V. "CURRENT-MODE SIGNAL PROCESSING CIRCUITS." Proceedings of the Estonian Academy of Sciences. Engineering 3, no. 4 (1997): 237. http://dx.doi.org/10.3176/eng.1997.4.01.

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5

Chen, Walter Y., and Richard A. Haddad. "Dual mode adaptive signal processing." Computers & Electrical Engineering 18, no. 3-4 (May 1992): 261–75. http://dx.doi.org/10.1016/0045-7906(92)90019-a.

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6

Gallard, Herve´, Joseph de Laat, and Bernard Legube. "Influence du pH sur la vitesse d'oxydation de compose´s organiques par FeII/H2O2. Me´canismes re´actionnels et mode´lisation." New Journal of Chemistry 22, no. 3 (1998): 263–68. http://dx.doi.org/10.1039/a708335a.

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7

Ladinig, Olivia, and David Huron. "Minor mode cuing: Do composers signal minor mode sooner than major mode?" Psychomusicology: Music, Mind, and Brain 23, no. 2 (2013): 117–22. http://dx.doi.org/10.1037/pmu0000007.

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8

Reau, J. M., J. Senegas, and M. El Omari. "Corre´lations entre proprie´te´se´lectriques et structurales de solutions solides de type fluorinea`exce`s d'anions: Essai de mode`lisation." Journal of Solid State Chemistry 84, no. 2 (February 1990): 253–70. http://dx.doi.org/10.1016/0022-4596(90)90324-q.

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9

Mardiono, Djoko Anwar, Gunawan Toto Hadiyanto, and Intan Kumala Sari. "Penggunaan Common-Mode Filter dan Differential-Mode Filter Pada EMI Driver Lampu LED." Zona Teknik: Jurnal Ilmiah 15, no. 2 (December 29, 2021): 1. http://dx.doi.org/10.37776/zt.v15i2.811.

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Power Energy efficiency for public application commonly used driver IC that operate by (Pulse Width Modulation) PWM, The effect of this implementation will generate EMI (Electromagnetic Interference) that can make radio signal distortion or other electronic distortion in the around device area. The action to reduce the signal distortions shall use Filter implementation in the electronic device circuit. The filter to reduce signal distortion are power line filter or ferrite beads filter. Power line filter used for reduce and to filtering noise signal from Power line source from PLN power line or from power line distribution Conduction emission., The ferrite beads filter implementation for noise reduction or filtering from Source power supply to load. Implement of both filters at the circuit diagram will impact to reduce noise signal that make distortion to the signal source.

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10

Toumazou, Chris, John Lidgey, and Brett Wilson. "Editorial. Current-mode analogue signal processing." IEE Proceedings G Circuits, Devices and Systems 137, no. 2 (1990): 61. http://dx.doi.org/10.1049/ip-g-2.1990.0013.

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11

Zhou, Yang, and Han Su. "Research on mode-coupled multi-mode Fiber mode-division in multiplexing transmission system." Journal of Physics: Conference Series 2246, no. 1 (April 1, 2022): 012034. http://dx.doi.org/10.1088/1742-6596/2246/1/012034.

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Abstract The mode coupling and random loss between different modes have important effects on the reliability of the multimode fiber-based mode division multiplexing transmission system. Using the VPI optical communication simulation platform, a short-distance analog-division multiplexing transmission system based on multimode fiber was designed and built. By setting the relevant parameters of mode coupling and random loss caused by bending, the quality of the eye diagram of the received signal is analyzed by the photoelectric signal analyzer at the receiving end. The experimental results show that the mode coupling has great influence on the anti-noise performance and anti-inter-symbol interference performance of the multimode fiber-based transmission system, and the random loss has great influence on the anti-noise performance of the system, this effect is more obvious in high-order linear polarization mode fiber.

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12

Ray, Papia, Rajesh Kumar Lenka, and Monalisa Biswal. "Frequency mode identification using modified masking signal-based empirical mode decomposition." IET Generation, Transmission & Distribution 13, no. 8 (April 23, 2019): 1266–76. http://dx.doi.org/10.1049/iet-gtd.2018.5527.

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13

Sotov, L. S., V. N. Kharin, and A. L. Khvalin. "Operation mode detectors for random signal generators." Automation and Remote Control 71, no. 5 (May 2010): 876–79. http://dx.doi.org/10.1134/s0005117910050140.

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14

Klionskiy, Dmitry, Mikhail Kupriyanov, and Dmitry Kaplun. "Signal denoising based on empirical mode decomposition." Journal of Vibroengineering 19, no. 7 (November 15, 2017): 5560–70. http://dx.doi.org/10.21595/jve.2017.19239.

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15

Kokanos, Barrie L., and George G. Karady. "Associate Hermite Expansion Small Signal Mode Estimation." IEEE Transactions on Power Systems 25, no. 2 (May 2010): 999–1006. http://dx.doi.org/10.1109/tpwrs.2009.2032551.

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16

Silver, Michael, Yu-Ping Huang, Carsten Langrock, Martin M. Fejer, Prem Kumar, and Gregory S. Kanter. "Three-Signal Temporal-Mode Selective Upconversion Demultiplexing." IEEE Photonics Technology Letters 31, no. 21 (November 1, 2019): 1749–52. http://dx.doi.org/10.1109/lpt.2019.2944636.

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17

Davidson, G. W., and I. Cumming. "Signal properties of spaceborne squint-mode SAR." IEEE Transactions on Geoscience and Remote Sensing 35, no. 3 (May 1997): 611–17. http://dx.doi.org/10.1109/36.581976.

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18

Hou, Bingchang, Dong Wang, Tangbin Xia, Zhike Peng, and Kwok-Leung Tsui. "Difference mode decomposition for adaptive signal decomposition." Mechanical Systems and Signal Processing 191 (May 2023): 110203. http://dx.doi.org/10.1016/j.ymssp.2023.110203.

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19

KILIÇ, RECAI. "SC-CNN BASED MULTIFUNCTION SIGNAL GENERATOR." International Journal of Bifurcation and Chaos 17, no. 12 (December 2007): 4387–93. http://dx.doi.org/10.1142/s0218127407020038.

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This paper presents a very versatile multifunction signal generator tool. The proposed generator is based on State Controlled Cellular Neural Network (SC-CNN) based Chua's circuit and it has two signal generation modes, namely CM (Chaos Mode) and FM (Function Mode). While the generator is able to produce nonlinear chaotic waveforms in Chaos Mode, it is also able to generate other classical sinusoidal, triangle and square waveforms in Function Mode. The proposed design idea has been validated through computer simulations and laboratory experiments. Future studies with the proposed generator tool will contribute to further developments in SC-CNN based engineering applications.

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20

Li, Lingyun, Chanchan Qin, Guoqing Li, Shengbo Hu, Yike Xie, and Zhenwei Lei. "Transformer-based radio modulation mode recognition." Journal of Physics: Conference Series 2384, no. 1 (December 1, 2022): 012017. http://dx.doi.org/10.1088/1742-6596/2384/1/012017.

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Abstract The wireless communication technology develop rapidly, signal modulation mode technology becomes increasingly important. Therefore, in order to enhance the ability of radio signal modulation mode recognition in the complex electromagnetic environment, a novel radio signal modulation mode recognition method is proposed on account of Transformer network. Firstly, raw data were split with a fixed size window. Then, the segmented data was projected into a vector sequence and fed into the Transformer module to model and mine the relationship between signal waveform and modulation method to achieve identification. Extensive experiments were conducted on the RML2016.10a data set generated by GNU radio in the real system. The experimental results show that the proposed Transformer-B/8×2 achieves optimal results for modulation mode recognition with signal-to-noise from -20dB to 18dB, and recognition accuracy reaches 86.75%, verifying the practicability and validity of the forenamed algorithm.

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21

Ge, Hengqing, Guibin Chen, Haichun Yu, Huabao Chen, and Fengping An. "Theoretical Analysis of Empirical Mode Decomposition." Symmetry 10, no. 11 (November 10, 2018): 623. http://dx.doi.org/10.3390/sym10110623.

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This work suggests a theoretical principle about the oscillation signal decomposition, which is based on the requirement of a pure oscillation component, in which the mean zero is extracted from the signal. Using this principle, the validity and robustness of the empirical mode decomposition (EMD) method are first proved mathematically. This work also presents a modified version of EMD by the interpolation solution, which is able to improve the frequency decomposition of the signal. The result shows that it can provide a primary theoretical basis for the development of EMD. The simulation signal verifies the effectiveness of the EMD algorithm. At the same time, compared with the existing denoising algorithm, it has achieved good results in the denoising of rolling bearing fault signals. It contributes to the development and improvement of adaptive signal processing theory in the field of fault diagnosis. It provides practical value research results for the rapid development of adaptive technology in the field of fault diagnosis.

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22

Arik, Sercan Ö., Daulet Askarov, and Joseph M. Kahn. "Effect of Mode Coupling on Signal Processing Complexity in Mode-Division Multiplexing." Journal of Lightwave Technology 31, no. 3 (February 2013): 423–31. http://dx.doi.org/10.1109/jlt.2012.2234083.

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23

Klionskiy, D. M., D. I. Kaplun, and V. V. Geppener. "Empirical Mode Decomposition for Signal Preprocessing and Classification of Intrinsic Mode Functions." Pattern Recognition and Image Analysis 28, no. 1 (January 2018): 122–32. http://dx.doi.org/10.1134/s1054661818010091.

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24

Lian, Jijian, Zhuo Liu, Haijun Wang, and Xiaofeng Dong. "Adaptive variational mode decomposition method for signal processing based on mode characteristic." Mechanical Systems and Signal Processing 107 (July 2018): 53–77. http://dx.doi.org/10.1016/j.ymssp.2018.01.019.

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25

Baranov, Pavel, Valeriy Borikov, Edvard Tsimbalist, and Bien Bui Duc. "Decrease uncertainty of measuring small differential signal against large common-mode signal." MATEC Web of Conferences 102 (2017): 01006. http://dx.doi.org/10.1051/matecconf/201710201006.

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26

TSUI, PO-HSIANG, CHIEN-CHENG CHANG, and NORDEN E. HUANG. "NOISE-MODULATED EMPIRICAL MODE DECOMPOSITION." Advances in Adaptive Data Analysis 02, no. 01 (January 2010): 25–37. http://dx.doi.org/10.1142/s1793536910000410.

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The empirical mode decomposition (EMD) is the core of the Hilbert–Huang transform (HHT). In HHT, the EMD is responsible for decomposing a signal into intrinsic mode functions (IMFs) for calculating the instantaneous frequency and eventually the Hilbert spectrum. The EMD method as originally proposed, however, has an annoying mode mixing problem caused by the signal intermittency, making the physical interpretation of each IMF component unclear. To resolve this problem, the ensemble EMD (EEMD) was subsequently developed. Unlike the conventional EMD, the EEMD defines the true IMF components as the mean of an ensemble of trials, each consisting of the signal with added white noise of finite, not infinitesimal, amplitude. In this study, we further proposed an extension and alternative to EEMD designated as the noise-modulated EMD (NEMD). NEMD does not eliminate mode but intensify and amplify mixing by suppressing the small amplitude signal but the larger signals would be preserved without waveform deformation. Thus, NEMD may serve as a new adaptive threshold amplitude filtering. The principle, algorithm, simulations, and applications are presented in this paper. Some limitations and additional considerations of using the NEMD are also discussed.

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27

TOUMAZOU, CHRISTOFER. "ANALOGUE SIGNAL PROCESSING: THE “CURRENT” WAY OF THINKING." International Journal of High Speed Electronics and Systems 03, no. 03n04 (September 1992): 297–336. http://dx.doi.org/10.1142/s0129156492000126.

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This paper presents a tutorial review of the current-mode approach to analogue electronic circuit design, in particular some of the author’s own research over the past decade covering the development of a new generation of technology specific current-mode analogue signal processing. In this paper various technologies are represented with key current-mode building blocks ranging from current-conveyors, current-feedback operational amplifiers, linear transconductance amplifiers to applications ranging from current-mode active filters to low-noise current-mode optical preamplifiers. Advantages, future trends and perspectives of the current-mode approach are highlighted throughout the paper. The theoretical basis for many of the examples dates back many years but it is only recently due to advances in process technology that many of these techniques have now become a practical reality.

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28

Meignen, Sylvain, Thomas Oberlin, Philippe Depalle, Patrick Flandrin, and Stephen McLaughlin. "Adaptive multimode signal reconstruction from time–frequency representations." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2065 (April 13, 2016): 20150205. http://dx.doi.org/10.1098/rsta.2015.0205.

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This paper discusses methods for the adaptive reconstruction of the modes of multicomponent AM–FM signals by their time–frequency (TF) representation derived from their short-time Fourier transform (STFT). The STFT of an AM–FM component or mode spreads the information relative to that mode in the TF plane around curves commonly called ridges . An alternative view is to consider a mode as a particular TF domain termed a basin of attraction . Here we discuss two new approaches to mode reconstruction. The first determines the ridge associated with a mode by considering the location where the direction of the reassignment vector sharply changes, the technique used to determine the basin of attraction being directly derived from that used for ridge extraction. A second uses the fact that the STFT of a signal is fully characterized by its zeros (and then the particular distribution of these zeros for Gaussian noise) to deduce an algorithm to compute the mode domains. For both techniques, mode reconstruction is then carried out by simply integrating the information inside these basins of attraction or domains.

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29

QIAN, TAO, LIMING ZHANG, and HONG LI. "MONO-COMPONENTS VS IMFs IN SIGNAL DECOMPOSITION." International Journal of Wavelets, Multiresolution and Information Processing 06, no. 03 (May 2008): 353–74. http://dx.doi.org/10.1142/s0219691308002392.

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The concepts of intrinsic mode functions and mono-components are investigated in relation to the empirical mode decomposition. Mono-components are defined to be the functions for which non-negative analytic instantaneous frequency is well defined. We show that a great variety of functions are mono-components based on which adaptive decomposition of signals are theoretically possible. We justify the role of empirical mode decomposition in signal decomposition in relation to mono-components.

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30

Rezaee, Mousa, and Amin Taraghi Osguei. "Improving empirical mode decomposition for vibration signal analysis." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 231, no. 12 (February 3, 2016): 2223–34. http://dx.doi.org/10.1177/0954406216630004.

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In this paper, the empirical mode decomposition as a signal processing method has been studied to overcome one of its shortcomings. In the previous studies, some improvements have been made on the empirical mode decomposition and it has been applied for condition monitoring of mechanical systems. These improvements include elimination of mode mixing and restraining of end effect in empirical mode decomposition method. In this research, to increase the accuracy of empirical mode decomposition, a new local mean has been proposed in the sifting process. Through the proposed local mean, the overshoot and undershoot problems in defining the local mean of common algorithm are alleviated. Meanwhile, it is capable to separate the components with close frequencies. Through the analysis of simulated signals via the new algorithm, it is shown that the accuracy is improved. Finally, empirical mode decomposition-based fault diagnosis approach has been applied to a vibration signal obtained from a faulty gearbox. The results show that the proposed method can resolve the effects of damage in vibration signals better than the common empirical mode decomposition method and helps for the isolation and localization of the fault.

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31

Yi, Jun, Dong Cao, HE Xiao, and Xin Long Zhang. "Study of Novel Percussion Medical Signal Measurement Mode." Applied Mechanics and Materials 475-476 (December 2013): 99–102. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.99.

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This paper presents one percussion sound signal collection system model. The percussion sound signal collection device was designed. The sound collector was introduced in detail. Through analyzing four kinds of different percussion sound, the accuracy of this model is verified. The results showed that this collection model and percussion sounds signal processing method can be accurate and effective. The experimental results are consistent with the theoretical value. This research provides one modern applications for the percussion in a new way.

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32

Аl-Мashhadani, Mohammad Abdulrahman, and Alexander Alexandrovich Lobaty. "Fuzzification Mode for Signal in Nonlinear Stochastic Systems." International Journal of Information Technology, Control and Automation 3, no. 1 (January 31, 2013): 71–83. http://dx.doi.org/10.5121/ijitca.2013.3106.

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33

Yadav, Himani, Sanjeev Seth, and Himani Yadav. "Analog Signal Processing Using Current Mode Computational Circuits." Journal of Analog and Digital Communications 7, no. 2 (August 29, 2022): 20–28. http://dx.doi.org/10.46610/joadc.2022.v07i02.004.

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In this study, enhanced linearity and wide linear range current adder and subtractor circuits based on cascode current mirrors are presented. Among other analogue signal processing devices, the described circuits can be employed in operational transconductance amplifiers (OTA), Gm-C filters, and amplifiers. To enhance current mirroring performance, the suggested circuits use the cascode current mirror topology. A 1.8-volt supply and TSMC 0.18-micron CMOS technology were used to model the suggested circuits. The suggested circuits have an allowed error percentage of less than 2.5% and perform well in the current range of 0 to 80 A. The outcomes of the SPICE simulation have shown how well the proposed circuits work.

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34

Yao, Cheng-Kai, Ying-Huan Chen, Yibeltal Chanie Manie, Mekuanint Agegnehu Bitew, and Peng-Chun Peng. "Microwave signal generation with discrete mode laser diode." Laser Physics Letters 19, no. 5 (April 1, 2022): 056201. http://dx.doi.org/10.1088/1612-202x/ac60a4.

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Abstract Microwave signals with low phase noise can be broadly used in communication systems, satellite communications, and radar systems. Discrete mode laser diode (DM-LD) has the capacity to generate signals that meet the above requirements. Moreover, it has the following advantages such as stable operation over a wide temperature range, very high side mode suppression ratio, low sensitivity to optical feedback, and narrow linewidth. In this paper, we proposed and experimentally demonstrated DM-LD for generating the second harmonic signal in the self-starting microwave generation system. The results show that DM-LD effectively reduces the single sideband (SSB) phase noise of the fundamental signals and its second harmonic signals better than the same designed experimental system using a distributed feedback LD, which reduces the SSB noise of the fundamental signal/its second harmonic signal by over 16/22 dB, 18/22 dB, 13/19 dB at a frequency offset of 10 kHz, 100 kHz, and 1 MHz, respectively.

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35

Li, Fangyu, Bo Zhang, Sumit Verma, and Kurt J. Marfurt. "Seismic signal denoising using thresholded variational mode decomposition." Exploration Geophysics 49, no. 4 (August 2018): 450–61. http://dx.doi.org/10.1071/eg17004.

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36

Gao, Ya Tian, Li Hua Wang, Xiu Jie Miao, and Jian Cheng Leng. "Application of Empirical Mode Decomposition to ACFM Signal." Advanced Materials Research 889-890 (February 2014): 761–65. http://dx.doi.org/10.4028/www.scientific.net/amr.889-890.761.

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37

Shahrivar, Farid, and Jack G. Bouwkamp. "Signal Separation Method for Tower Mode Shape Measurement." Journal of Structural Engineering 115, no. 3 (March 1989): 707–23. http://dx.doi.org/10.1061/(asce)0733-9445(1989)115:3(707).

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38

Foubert, Wim, Carine Neus, Leo Van Biesen, and Yves Rolain. "Exploiting the Phantom-Mode Signal in DSL Applications." IEEE Transactions on Instrumentation and Measurement 61, no. 4 (April 2012): 896–902. http://dx.doi.org/10.1109/tim.2011.2174100.

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39

Islam Molla, Md Khademul, Somlal Das, Md Ekramul Hamid, and Keikichi Hirose. "Empirical Mode Decomposition for Advanced Speech Signal Processing." Journal of Signal Processing 17, no. 6 (2013): 215–29. http://dx.doi.org/10.2299/jsp.17.215.

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40

Wolf, Kurt Bernardo. "Mode analysis and signal restoration with Kravchuk functions." Journal of the Optical Society of America A 26, no. 3 (February 12, 2009): 509. http://dx.doi.org/10.1364/josaa.26.000509.

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41

Wang, Yanxue, Fuyun Liu, Zhansi Jiang, Shuilong He, and Qiuyun Mo. "Complex variational mode decomposition for signal processing applications." Mechanical Systems and Signal Processing 86 (March 2017): 75–85. http://dx.doi.org/10.1016/j.ymssp.2016.09.032.

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42

Tang, W., F. C. Lee, and R. B. Ridley. "Small-signal modeling of average current-mode control." IEEE Transactions on Power Electronics 8, no. 2 (April 1993): 112–19. http://dx.doi.org/10.1109/63.223961.

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43

Andrade, Adriano O., Slawomir Nasuto, Peter Kyberd, Catherine M. Sweeney-Reed, and F. R. Van Kanijn. "EMG signal filtering based on Empirical Mode Decomposition." Biomedical Signal Processing and Control 1, no. 1 (January 2006): 44–55. http://dx.doi.org/10.1016/j.bspc.2006.03.003.

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44

Amirkhanzadeh, R., A. Khoei, and Kh Hadidi. "A mixed-signal current-mode fuzzy logic controller." AEU - International Journal of Electronics and Communications 59, no. 3 (June 2005): 177–84. http://dx.doi.org/10.1016/j.aeue.2004.11.019.

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45

Stoica, Petre, and Magnus Jansson. "On Forward–Backward MODE for Array Signal Processing." Digital Signal Processing 7, no. 4 (October 1997): 239–52. http://dx.doi.org/10.1006/dspr.1997.0298.

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46

Fu, Min, Jiawei Wang, Zhixian Li, Weiyi Yuan, Zefeng Wang, and Zilun Chen. "Research on Adjustable Ring-Mode Fiber Signal Combiner." Photonics 10, no. 2 (February 12, 2023): 195. http://dx.doi.org/10.3390/photonics10020195.

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Nowadays, fiber laser has been widely used in industrial processing, especially in welding, cutting and other fields, and the appearance of adjustable ring-mode fiber laser improves effectively the quality of processing. In this paper, a (6 + 1) × 1 adjustable ring-mode fiber signal combiner is developed based on the technology of fiber cladding corrosion. The test results show that under the same injection condition, the beam quality transmitted through the central port of the combiner is degraded by only 8.3% compared with that transmitted through a single 50/250 μm fiber. It is proven to be feasible to maintain the beam quality of the (6 + 1) × 1 combiner by fiber corrosion technology. In order to improve the power of the central port of the (6 + 1) × 1 adjustable ring-mode combiner, a 3 × 1 fiber signal combiner and the central port of (6 + 1) × 1 combiner are cascaded. The output beam quality is M2 = 4.45 and the overall transmission efficiency is greater than 95%. This combiner can choose the mode of the output beam according to the actual application requirements, so as to achieve a better application effect.

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47

Wang, Jian Guo, Qun E, Ke Ming Yao, and Xin Long Wan. "Empirical Mode Decomposition on Geometry Signal Based Spherical Parameterization." Advanced Materials Research 998-999 (July 2014): 860–63. http://dx.doi.org/10.4028/www.scientific.net/amr.998-999.860.

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A novel method based onEmpirical Mode Decomposition(EMD) is approached to process the geometry signal. The main idea is to decompose the signal into some different detail components called Intrinsic Mode Function (IMF). The key steps are as follows: First, the signal is spherical parameterization; Second it is transformed into the plane signal and sampled regularly; Third, the translated signal is processed as an image using Bid-Empirical Mode Decomposition, getting several image IMFs; Finally, invert mapping these IMFs to geometry signal and getting the geometry signal’s IMFs.We demonstrate the power of the algorithms through a number of application examples including de-noising and enhancement.

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48

Luo Junwen, 罗均文, 李云霞 Li Yunxia, 石磊 Shi Lei, 蒙文 Meng Wen, 许振宇 Xu Zhenyu, and 薛阳 Xue Yang. "Co-Fiber-Transmission Technology for Quantum Signal and Classical Optical Signal Based on Mode Division Multiplexing in Few-Mode Fiber." Laser & Optoelectronics Progress 54, no. 2 (2017): 022702. http://dx.doi.org/10.3788/lop54.022702.

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49

Xiong, Qing Song, Zhao Hua Wu, Pin Chen, and Sheng Zhang. "Analysis of Characteristic of Microstrip Signal Loss in Course of Signal Transmission." Advanced Materials Research 194-196 (February 2011): 2229–32. http://dx.doi.org/10.4028/www.scientific.net/amr.194-196.2229.

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The effect of loss of transmission line on the transmission signal can’t be ignored in microwave circuits. Based on the theory of loss and microwave network principle, the effect of the width, parallel length and space of transmission lines on the scattering parameters’ insertion loss is analyzed in perspective of scattering parameters of the odd mode and even mode. The simulation results show that: when the other parameters are fixed, both the characteristic impedance and the conductor loss decrease non-linearly with the line width broadening; due to the coupling effect between micro-strip lines, the first trough frequency of the scattering parameter S21 curved line, that is the point the signal energy attenuate most seriously, decreases linearly with line width broadening and increases non- linearly with line spaces broadening.

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50

Konpang, Jessada, and Natchayathorn Wattikornsirikul. "Four-Port Dual-Mode Diplexer with High Signal Isolation." Active and Passive Electronic Components 2020 (February 10, 2020): 1–5. http://dx.doi.org/10.1155/2020/4032673.

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Abstract:

An ease of four-port dual-mode diplexer with high signal isolation is presented. A compact dual-mode diplexer with high signal isolation between the Rx and Tx modules is achievable by only using one resonator filter topology. Two back-to-back dual-mode diplexers have a 180° phase shift in one branch. The high isolation can be achieved by amplitude and phase cancellation technique. The delayed transmission line can be easily achieved by the phase shifter. The simulated and measured four-port dual-mode diplexers are designed at the centre frequency of Rx/Tx at 1.95 GHz and 2.14 GHz, respectively. The measured results of Rx/Tx dual-mode diplexer devices are presented with 47.1 dB Rx/Tx isolation. This four-port dual-mode diplexer achieves the isolation (S32) of more than 24.1 dB when compared with the conventional three-port dual-mode diplexer structure.

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