Relevant bibliographies by topics / Signal processing Mathematical models

Contents

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

Academic literature on the topic 'Signal processing Mathematical models'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 January 2023

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Journal articles on the topic "Signal processing Mathematical models"

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Rogozinsky, G., M. Chesnokov, and A. Kutlyiarova. "Some New Mathematical Models of Synthesized Sound Signals." Proceedings of Telecommunication Universities 8, no. 2 (June 30, 2022): 76–81. http://dx.doi.org/10.31854/1813-324x-2022-8-2-76-81.

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Modern sound synthesis systems make it possible to implement various signal generation algorithms of higher complexity. The theory of sound synthesis actively uses the mathematical apparatus of analog and digital radio engineering and signal processing, however, it should be noted that the classical signal models used in acoustics are not adequate to real-world synthesized signals, mainly due to the significant complexity of the latter. This article presents some models of synthesized signals typical for practical use.
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Monakov, A. A., and A. A. Tarasenkov. "Comparative Analysis of Mathematical Models of Tracking Radio Altimeters." Journal of the Russian Universities. Radioelectronics 25, no. 4 (September 29, 2022): 72–80. http://dx.doi.org/10.32603/1993-8985-2022-25-4-72-80.

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Introduction. Tracking radio altimeters of low altitudes are widely used in civil aviation. These devises use periodic frequency modulated continuous wave (FMCW) signals, while altitude measurements are based on processing the beat signal processing. For this purpose, a closed automatic control loop is arranged to maintain the frequency of the beat signal at a fixed level by changing parameters of the transmitted signal (the frequency deviation or the modulation period). An alternative approach to arranging the tracking loop for altitude variations is based on the use of a phase locked loop (P
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Qu, Qiuhui. "Application of MATLAB in signal and system." SHS Web of Conferences 145 (2022): 01029. http://dx.doi.org/10.1051/shsconf/202214501029.

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Signal and system course is an important professional basic course for electronic information and communication majors. Signal and system are abstract concepts, which are described by mathematical models. In daily life, simple signals can be calculated or drawn manually, but complex signals are difficult to be accurately processed. Matlab contains graphics processing and symbol operation functions, which provides us with powerful tools to solve the above problems. This paper will introduce how to use Matlab to express, calculate and process signals, and realize the systematic analysis of signa
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Tague, John A., and Kerry D. Schutz. "Seismic transient deconvolution with model‐based signal processing." GEOPHYSICS 62, no. 4 (July 1997): 1321–30. http://dx.doi.org/10.1190/1.1444234.

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Short duration seismic disturbances, obscured by earth noise and distorted by the seismometers used to measure them, can be reconstructed using model‐based signal processing. “Model based” means that mathematical models of the seismic transient, earth noise, and seismometer dynamics are infused into the signal processor that estimates the disturbance. The processor imposes no predetermined structure on the transient and the earth noise need not be white. Model‐based processors produce good quality estimates for a broad class of transient waveforms.
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Sharko, Artem. "MODELS AND METHODS OF PROCESSING OF INFORMATION ON LOADS OF ACOUSTIC SIGNALS IN TECHNICAL DIAGNOSTIC SYSTEMS." Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska 8, no. 3 (September 25, 2018): 15–18. http://dx.doi.org/10.5604/01.3001.0012.5276.

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The paper presents one-dimensional discrete-continuous model of power spectrum estimation of the acoustic emission signal, that allows filtering the oscillating components of the acoustic emission signals. The mathematical formalism describing the environment was discussed, initiating the signals of acoustic emission. The problem of spectral analysis and synthesis of acoustic emission signals was solved with the help of Fourier transform. The dependence of acoustic vibrations spectra on the size of the medium parameters and microstructure has been discussed, as well.
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Lavanya, S., S. Prabakaran, and N. Ashok Kumar. "A Deep Learning Technique for Detecting High Impedance Faults in Medium Voltage Distribution Networks." Engineering, Technology & Applied Science Research 12, no. 6 (December 1, 2022): 9477–82. http://dx.doi.org/10.48084/etasr.5288.

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Utility companies always struggle with the High Impedance Fault (HIF) in the electrical distribution systems. In this article, the current signal is seen in situations involving 10,400 different samples, with and without HIF, like linear, non-linear load, and capacitance switching. A better method that processes signals very fast and with low sample rates, requiring less memory and computational labor, is demonstrated by Mathematical Morphology (MM). For HIF identification, Deep Convolution Neural Networks (DCNNs) are being developed. This paper presents a novel method for signal processing wi
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Beardah, C. C., and R. M. Thomas. "Two mathematical models of unconfined detonation and their numerical solution." Circuits, Systems, and Signal Processing 13, no. 2-3 (June 1994): 155–65. http://dx.doi.org/10.1007/bf01188103.

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Lomakin, A., D. Pantenkov, and V. Sokolov. "Mathematical Models of Satellite Communication Systems with Unmanned Aerial Vehicles and Counter-Means of Radio Control. Part 2." Proceedings of Telecommunication Universities 5, no. 4 (2019): 37–48. http://dx.doi.org/10.31854/1813-324x-2019-5-4-37-48.

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The article is devoted to the issues of stealth satellite radio channels with unmanned aerial vehicles (UAV) and it is consists of two parts. In the first part of this article the following questions are considered: the general statement of a system development problem of satellite model communication providing its stealth functioning by means of radio monitoring is carried out; the mathimatical apparatus for the assessing the effectiveness of ensuring spatial selectivity in the organization of satellite communication lines at hidden objects of their functioning is presented; the functioning m
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Al-Suod, Mahmoud, Abdullah Eial Awwad, Alaa Al-Quteimat, and Oleksandr Ushkarenko. "Method for describing signal conversion processes in analog electronic systems." Bulletin of Electrical Engineering and Informatics 11, no. 1 (February 1, 2022): 82–92. http://dx.doi.org/10.11591/eei.v11i1.3545.

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One of the main tasks of information technology is to improve existing and develop new methods for formal recording of various dynamic logical operations of analog and digital signal conversion in electronic control systems, acquisition, and processing of information. The stage of formal recording of any signal transformation process must be presented in the form of analytic symbols, the sequence of which must form a fully functional mathematical model. The improved method of the signals conversion processes description based on a representation of the mathematical models of the electronic cir
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Marano, Stefano, and Marco Marano. "Frontiers in hemodialysis: Solutions and implications of mathematical models for bicarbonate restoring." Biomedical Signal Processing and Control 52 (July 2019): 321–29. http://dx.doi.org/10.1016/j.bspc.2019.02.029.

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Dissertations / Theses on the topic "Signal processing Mathematical models"

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Fabrizio, Giuseppe Aureliano. "Space-time characterisation and adaptive processing of ionospherically-propagated HF signals /." Title page, table of contents and abstract only, 2000. http://web4.library.adelaide.edu.au/theses/09PH/09phf129.pdf.

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Cai, Qin. "Detecting Chaotic Signals with Nonlinear Models." PDXScholar, 1993. https://pdxscholar.library.pdx.edu/open_access_etds/4564.

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In this thesis we apply chaotic dynamic data analysis to the area of discrete time signal processing. A newly developed Hidden Filter Hidden Markov Model is introduced in detection of chaotic signals. Numerical experiments have verified that this novel nonlinear model outperforms linear AR model in detecting chaotic signals buried by noise having similar power spectra. A simple Histogram Model is proposed which can also be used to do detection on the data sets with chaotic behavior. Receiver Operating Characteristics for a variety of noise levels and model classes are reported.
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Webb, M. R. "Millimetre wave quasi-optical signal processing systems." Thesis, University of St Andrews, 1993. http://hdl.handle.net/10023/2827.

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The development of spatial signal processing techniques at millimetre wavelengths represents an area of science and technology that is new. At optical wavelengths, spatial signal processing techniques are well developed and are being applied to a variety of situations. In particular they are being used in pattern recognition systems with a great deal of success. At millimetre wavelengths, the kind of technology used for signal transport and processing is typically either waveguide based or quasi-optically based, or some hybrid of the two. It is the use of quasi-optical methods that opens up th
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Zhang, Zhiguo, and 張治國. "On bandwidth and scale selection in processing of time-varying signalswith applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39707465.

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Selén, Yngve. "Model selection /." Uppsala : Univ. : Dept. of Information Technology, Univ, 2004. http://www.it.uu.se/research/reports/lic/2004-003/.

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Stoffell, Kevin M. "Implementation of a Quadrature Mirror Filter Bank on an SRC reconfigurable computer for real-time signal processing." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FStoffell.pdf.

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Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, September 2006.<br>Thesis Advisor(s): Douglas J. Fouts. "September 2006." Includes bibliographical references (p. 111-112). Also available in print.
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洪觀宇 and Roy Hung. "Time domain analysis and synthesis of cello tones based on perceptual quality and playing gestures." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31215348.

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Li, Xiao, and 李驍. "Channel estimation and timing synchronization in cooperative communication systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42841835.

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Sadeghi, Parastoo School of Electrical Engineering And Telecommunications UNSW. "Modelling, information capacity, and estimation of time-varying channels in mobile communication systems." Awarded by:University of New South Wales. School of Electrical Engineering And Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/32310.

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In the first part of this thesis, the information capacity of time-varying fading channels is analysed using finite-state Markov channel (FSMC) models. Both fading channel amplitude and fading channel phase are modelled as finite-state Markov processes. The effect of the number of fading channel gain partitions on the capacity is studied (from 2 to 128 partitions). It is observed that the FSMC capacity is saturated when the number of fading channel gain partitions is larger than 4 to 8 times the number of channel input levels. The rapid FSMC capacity saturation with a small number of fading ch
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Yang, Yang. "2D signal processing: efficient models for spectral compressive sensing & single image reflection suppression." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6667.

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Two efficient models in two-dimensional signal processing are proposed in the thesis. The first model deals with large scale spectral compressive sensing in continuous domain, which aims to recover a 2D spectrally sparse signal from partially observed time samples. The signal is assumed to be a superposition of s complex sinusoids. We propose a semidefinite program for the 2D signal recovery problem. Our model is able to handle large scale 2D signals of size 500*500, whereas traditional approaches only handle signals of size around 20*20. The second model deals with the problem of single image
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Books on the topic "Signal processing Mathematical models"

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Solo, Victor. Adaptive signal processing algorithms: Stability and performance. Englewood Cliffs, N.J: Prentice Hall, 1995.

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Signals and systems in biomedical engineering: Signal processing and physiological systems modeling. New York: Kluwer Academic/Plenum Publishers, 2000.

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Gromakov, I︠U︡ A. Optimalʹnai︠a︡ obrabotka radiosignalov bolʹshimi sistemami. Moskva: Ėko-Trendz, 2004.

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Statistical digital signal processing and modeling. New York: John Wiley & Sons, 1996.

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Numbers & notes: An introduction to musical signal processing. Portland, Ore: PSI Press, 2012.

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United States. Advanced Research Projects Agency., ed. An optical signal processing model for the interferometric fiber optic gyro. Santa Monica, CA: RAND, 1995.

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Hall, David L. Mathematical techniques in multisensor data fusion. Boston: Artech House, 1992.

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L, Hall David. Mathematical techniques in multisensor data fusion. Boston: Artech House, 1992.

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Signal processing for neuroscientists: Introduction to the analysis of physiological signals. Amsterdam: Elsevier/Academic Press, 2007.

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L, Hall David. Mathematical techniques in multi-sensor data fusion. 2nd ed. Boston: Artech House, 2004.

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Book chapters on the topic "Signal processing Mathematical models"

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Butler, John L., and Charles H. Sherman. "Mathematical Models for Acoustic Radiation." In Modern Acoustics and Signal Processing, 555–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39044-4_11.

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Gamba, Jonah. "Radar Waveforms and Their Mathematical Models." In Radar Signal Processing for Autonomous Driving, 37–51. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9193-4_4.

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Abraham, Douglas A. "Mathematical Statistics." In Modern Acoustics and Signal Processing, 251–305. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-92983-5_5.

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Fuhrmann, Paul A., and Uwe Helmke. "On the Use of Functional Models in Model Reduction." In Perspectives in Mathematical System Theory, Control, and Signal Processing, 177–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-93918-4_16.

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Gopi, E. S. "Mathematical Model of Time Varying Wireless Channel Model." In Digital Signal Processing for Wireless Communication using Matlab, 55–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82036-7_2.

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Brockett, Roger W. "Markov Models for Coherent Signals: Extrapolation in the Frequency Domain." In Perspectives in Mathematical System Theory, Control, and Signal Processing, 299–307. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-93918-4_27.

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Gopi, E. S. "Mathematical Model of the Time-Varying Wireless Channel." In Digital Signal Processing for Wireless Communication using Matlab, 1–50. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-20651-6_1.

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Stawiaski, Jean. "Optimal Path: Theory and Models for Vessel Segmentation." In Mathematical Morphology and Its Applications to Image and Signal Processing, 417–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21569-8_36.

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Jeulin, Dominique, and Pascal Laurenge. "Probabilistic Model of Rough Surfaces Obtained by Electro-Erosion." In Mathematical Morphology and its Applications to Image and Signal Processing, 289–96. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0469-2_33.

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Yang, Lei, Liang Li, Chie Muraki Asano, and Akira Asano. "Primitive and Grain Estimation Using Flexible Magnification for a Morphological Texture Model." In Mathematical Morphology and Its Applications to Image and Signal Processing, 190–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21569-8_17.

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Conference papers on the topic "Signal processing Mathematical models"

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"Session MA7b Mathematical Models for Image Processing." In Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. IEEE, 2004. http://dx.doi.org/10.1109/acssc.2004.1399104.

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Bouchoffra, D., and F. Ykhlef. "Mathematical models for machine learning and pattern recognition." In 2013 8th InternationalWorkshop on Systems, Signal Processing and their Applications (WoSSPA). IEEE, 2013. http://dx.doi.org/10.1109/wosspa.2013.6602331.

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Rohde, Steve M., William J. Williams, and Mitchell M. Rohde. "Application of Advanced Signal Processing Methods to Automotive Systems Testing." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59535.

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During the past twenty years there have been rapid developments in the creation and application of mathematical computer-based capabilities and tools (e.g., FEA) to simulate and synthesize vehicle systems. This has led to the concept of virtual product development. In parallel with the development of these tools, an equally sophisticated set of tools have been developed in the area of advanced signal processing. These tools, based upon mathematical and statistical modeling techniques, enable the extraction of useful information from data and have application throughout the entire vehicle creat
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Akman, Caglar, Okan Demir, and Tolga Sonmez. "Covid-19 SEIQR Spread Mathematical Model." In 2021 29th Signal Processing and Communications Applications Conference (SIU). IEEE, 2021. http://dx.doi.org/10.1109/siu53274.2021.9477975.

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Wu, Feilong, Wenjie Wang, Hui-Ming Wang, and Qinye Yin. "A unified mathematical model for spatial scrambling based secure wireless transmission and its wiretap method." In Signal Processing (WCSP 2011). IEEE, 2011. http://dx.doi.org/10.1109/wcsp.2011.6096860.

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Simsek, Mustafa, Ibrahim Delibalta, Lemi Baruh, and Suleyman S. Kozat. "Mathematical model of causal inference in Social Networks." In 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 2016. http://dx.doi.org/10.1109/siu.2016.7495952.

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Analoui, Morteza, and Shahram Jamali. "TCP fairness enhancement through a mathematical parametric model." In Signal Processing with Special Track on Biomedical Engineering (CCSP). IEEE, 2005. http://dx.doi.org/10.1109/ccsp.2005.4977166.

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Artyushenko, Vladimir Mikhaylovich, and Vladimir Ivanovich Volovach. "The Mathematical Models of Transformation non-Gaussian Random Processes in the non-Linear non-Inertial Elements." In 2022 24th International Conference on Digital Signal Processing and its Applications (DSPA). IEEE, 2022. http://dx.doi.org/10.1109/dspa53304.2022.9790780.

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Moghaddam, Mohsen Ebrahimi. "A Mathematical Model to Estimate Out of Focus Blur." In 2007 5th International Symposium on Image and Signal Processing and Analysis. IEEE, 2007. http://dx.doi.org/10.1109/ispa.2007.4383705.

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"A STUDY OF STOCHASTIC RESONANCE AS A MATHEMATICAL MODEL OF ELECTROGASTROGRAM." In International Conference on Bio-inspired Systems and Signal Processing. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003159504500453.

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Reports on the topic "Signal processing Mathematical models"

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Luo, Zhi-Quan. Mathematical Analysis of Signal Processing Capabilities of Wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada499991.

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Baraniuk, Richard G. Multiscale Statistical Models for Signal and Image Processing. Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada425177.

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Shubitidze, Fridon. A Complex Approach to UXO Discrimination: Combining Advanced EMI Forward Models and Statistical Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, January 2012. http://dx.doi.org/10.21236/ada578937.

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Burnett, G. C. Damage Detection and Identification of Finite Element Models Using State-Space Based Signal Processing a Summation of Work Completed at the Lawrence Livermore National Laboratory February 1999 to April 2000. Office of Scientific and Technical Information (OSTI), April 2000. http://dx.doi.org/10.2172/793960.

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Tanny, Josef, Gabriel Katul, Shabtai Cohen, and Meir Teitel. Micrometeorological methods for inferring whole canopy evapotranspiration in large agricultural structures: measurements and modeling. United States Department of Agriculture, October 2015. http://dx.doi.org/10.32747/2015.7594402.bard.

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Original objectives and revisions The original objectives as stated in the approved proposal were: (1) To establish guidelines for the use of micrometeorological techniques as accurate, reliable and low-cost tools for continuous monitoring of whole canopy ET of common crops grown in large agricultural structures. (2) To adapt existing methods for protected cultivation environments. (3) To combine previously derived theoretical models of air flow and scalar fluxes in large agricultural structures (an outcome of our previous BARD project) with ET data derived from application of turbulent transp
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Modlo, Yevhenii O., Serhiy O. Semerikov, Stanislav L. Bondarevskyi, Stanislav T. Tolmachev, Oksana M. Markova, and Pavlo P. Nechypurenko. Methods of using mobile Internet devices in the formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3677.

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An analysis of the experience of professional training bachelors of electromechanics in Ukraine and abroad made it possible to determine that one of the leading trends in its modernization is the synergistic integration of various engineering branches (mechanical, electrical, electronic engineering and automation) in mechatronics for the purpose of design, manufacture, operation and maintenance electromechanical equipment. Teaching mechatronics provides for the meaningful integration of various disciplines of professional and practical training bachelors of electromechanics based on the concep
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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real tim
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