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Journal articles on the topic 'MATLAB'

To see the other types of publications on this topic, follow the link: MATLAB.

Author: Grafiati

Published: 4 June 2021

Last updated: 30 July 2024

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1

Spiegelman, C. H. "MATLAB and the MATLAP Optimization Toolbok (Macintosh Version)." Chemometrics and Intelligent Laboratory Systems 19, no. 1 (May 1993): 128. http://dx.doi.org/10.1016/0169-7439(93)80090-5.

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2

Schreiber, Rob. "MATLAB." Scholarpedia 2, no. 7 (2007): 2929. http://dx.doi.org/10.4249/scholarpedia.2929.

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3

Beardah, Christian. "MATLAB 6 and Student Version of MATLAB." MSOR Connections 1, no. 4 (November 2001): 36–40. http://dx.doi.org/10.11120/msor.2001.01040036.

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4

Dubrau, Anton Willy, and Laurie Jane Hendren. "Taming MATLAB." ACM SIGPLAN Notices 47, no. 10 (November 15, 2012): 503–22. http://dx.doi.org/10.1145/2398857.2384653.

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5

Maryanti, Indra. "APPLICATION OF MATHLAB APPLICATIONS IN IMPROVING STUDENT COMPETENCE UMSU MATHEMATICS EDUCATION STUDY PROGRAM NUMERICAL METHOD COURSE 2019-2020 ACADEMIC YEAR." International Journal of Educational Review, Law And Social Sciences (IJERLAS) 1, no. 2 (November 22, 2021): 221–26. http://dx.doi.org/10.54443/ijerlas.v1i2.91.

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This study aims to describe the role of MATHLAB software in numerical method lectures, improve students' ability to solve numerical problems through learning assisted by MATHLAB software, improve students' abilities in formulating algorithms through learning assisted by MATHLAB software, improve students' abilities in programming through assisted learning MATLAB software; and describing student responses after numerical learning assisted by MATLAB software. This research is a quantitative research. To prove the hypothesis and answer the problems in this study, several statistical tests were carried out as follows:1. Test the description of the data, namely: making a data frequency table, testing the average value, and standard deviation.2. Prerequisite test, namely: normality test with Liliefors table and homogeneity test.3. Hypothesis testing, namely: statistical tests to see how much improvement in student competence is using the MATLAB software application in the numerical method course. The tests used are regression and correlation tests to see the increase in student competence using the MATLAB software application. The research method used is experimental. The population of this research is UMSU 7th semester students in the 2019/2020 academic year as many as 98 students.

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6

Foster, Kenneth R. "Matlab made easier and Testing with Matlab [Software Resources]." IEEE Spectrum 38, no. 2 (February 2001): 87–89. http://dx.doi.org/10.1109/mspec.2001.8820115.

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7

DOERR, CHRISTOPHER R. "MATLAB for Beginners." Optics and Photonics News 10, no. 7 (July 1, 1999): 41. http://dx.doi.org/10.1364/opn.10.7.000041.

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8

Römer, G. R. B. E., and A. J. Huis in ’t Veld. "Matlab Laser Toolbox." Physics Procedia 5 (2010): 413–19. http://dx.doi.org/10.1016/j.phpro.2010.08.068.

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9

Kadlec, J., and J. Kadlec. "MATLAB Transputer Bridge." IFAC Proceedings Volumes 27, no. 8 (July 1994): 1627. http://dx.doi.org/10.1016/s1474-6670(17)47952-3.

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10

Marcotte, Denis. "Cokriging with matlab." Computers & Geosciences 17, no. 9 (1991): 1265–80. http://dx.doi.org/10.1016/0098-3004(91)90028-c.

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11

Funt, Brian, Florian Ciurea, and John McCann. "Retinex in Matlab." Color and Imaging Conference 8, no. 1 (January 1, 2000): 112–21. http://dx.doi.org/10.2352/cic.2000.8.1.art00022.

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12

Verboven, Sabine, and Mia Hubert. "MATLAB library LIBRA." Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 4 (April 22, 2010): 509–15. http://dx.doi.org/10.1002/wics.96.

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13

Veettikazhy, Madhu, Anders Kragh Hansen, Dominik Marti, Stefan Mark Jensen, Anja Lykke Borre, Esben Ravn Andresen, Kishan Dholakia, and Peter Eskil Andersen. "BPM-Matlab: an open-source optical propagation simulation tool in MATLAB." Optics Express 29, no. 8 (March 31, 2021): 11819. http://dx.doi.org/10.1364/oe.420493.

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14

Pekh, P., S. Lavrenchuk, O. Miskevych, and R. Diachenko. "Порівняльний аналіз методів розв’язування диференціальних рівнянь засобами Matlab та Matlab Simulink." COMPUTER-INTEGRATED TECHNOLOGIES: EDUCATION, SCIENCE, PRODUCTION, no. 48 (October 1, 2022): 103–10. http://dx.doi.org/10.36910/6775-2524-0560-2022-48-16.

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В статті зроблена спроба проаналізувати методи розв’язування диференціальних рівнянь засобами Matlab та Matlab Simulink. Наведені коди програм, структурні схеми та результати моделювання двох диференціальних рівнянь.

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15

Gayev, Ye. "MATLAB-PROJECT “ANALOGUE WATCH”." Information Technologies in Education 4, no. 41 (December 2019): 34–47. http://dx.doi.org/10.14308/ite000707.

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16

Shrivastava, P. "Cloud Detection with MATLAB." Journal of Engineering Science and Technology Review 6, no. 1 (February 2013): 68–71. http://dx.doi.org/10.25103/jestr.061.13.

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17

M. Africa, Aaron Don. "Face Recognition Using MATLAB." International Journal of Advanced Trends in Computer Science and Engineering 8, no. 1.4 (September 15, 2019): 1110–16. http://dx.doi.org/10.30534/ijatcse/2019/17842019.

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18

KIM, Youngtae. "Physics Simulations with MATLAB." Physics and High Technology 23, no. 4 (April 30, 2014): 29. http://dx.doi.org/10.3938/phit.23.014.

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19

Voona, Venkata Nitin, Ennapureddy Sathwik, Tamire Satya Jayanth, and Thatikonda Rohan. "Brain Segmentation using MATLAB." International Journal of Innovative Technology and Exploring Engineering 11, no. 8 (July 30, 2022): 43–49. http://dx.doi.org/10.35940/ijitee.h9164.0711822.

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A surprising mass of tissue wherein some cells duplicates and develops wildly is calledcerebrum growth. It should be identified at a beginning phase utilizing X-ray or CT checked pictures when it is just about as little as conceivable in light of the fact that the growth might perhaps result to malignant growth. This paper, for the most part centers around identifying and limiting the growth locale existing in the cerebrum by proposed philosophy utilizing patient’s X-ray pictures. The proposed procedure comprises of different stages which assume an alternate parts to deliver the examination with at most precision. division is applied to obviously show the growth impacted locale in the X-ray pictures. There are two main objectives of our project: 1) To analyze brain tumor 2) If there is, specify the location of the tumor.

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20

Roberg, Penina, Gunnar Backstrom, and Patrick Marchand. "Practical Mathematics Using MATLAB." Mathematical Gazette 81, no. 491 (July 1997): 321. http://dx.doi.org/10.2307/3619232.

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21

Shiu, P., K. Chen, P. J. Giblin, and A. Irving. "Mathematical Explorations with MATLAB." Mathematical Gazette 83, no. 498 (November 1999): 558. http://dx.doi.org/10.2307/3621015.

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22

Pamungkas, Wahyu, Anggun Fitrian Isnawati, and Adi Kurniawan. "Modulasi Digital Menggunakan Matlab." JURNAL INFOTEL - Informatika Telekomunikasi Elektronika 4, no. 2 (November 10, 2012): 1. http://dx.doi.org/10.20895/infotel.v4i2.102.

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In telecommunication systems, the determination of the modulation system is an important method in the process of sending information from transmitter to receiver. In the simulation that is done using QPSK modulation system (Quadrature Phase Shift Keying), 8-QAM (Quadrature Amplitude Modulation), 16-QAM (16-Quadrature Amplitude Modulation) that uses AWGN (Additive White Gaussian Noise) channel in the transmission system uses MATLAB software. The execution of the simulation is aimed to describe how the characteristics of the waveform of each block of the modulator, to add noise in the AWGN channel and demodulator. Performance of modulation system testing is used BER (bit error ratio) method. Looking of the faults of comparison bits results of before and after the transmitted bits by using Monte Carlo simulation model. Testing on this simulation using the input data as much as 10.000 data symbols randomly and the level of Eb/No that is various for each modulation used. Performance results BER with the level of Eb / No at 1 dB of the simulated system modulation on the BER values obtained for QPSK 0.0570, 8-QAM at 0.1085 while the 16-QAM at 0.1582 and then the performance of QPSK modulation is the best. If the Eb / No is increased to 8 dB then the becomes BER QPSK smaller modulation is equal to 0.00035, the 8-QAM BER obtained at 0.0076, while the 16-QAM modulation to be 0.0139

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23

Aziz, Siti Hawa. "Polynomial Interpolation in Matlab." Journal of Engineering and Science Research 2, no. 4 (August 10, 2018): 12–19. http://dx.doi.org/10.26666/rmp.jesr.2018.4.3.

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The problem of constructing such a continuous function is called data fitting. Many times, data given only at discrete points. With interpolation, we seek a function that allows us to approximate f(x) such that functional values between the original data set values may be determined. The process of finding such a polynomial is called interpolation and one of the most important approaches used are Lagrange interpolating formula. In this study, researcher determining the polynomial interpolation by using Lagrange interpolating formula. Then, a mathematical modelling was built by using MATLAB programming to determine the polynomial interpolation for a given points using the Lagrange method. The result of the study showed that the manual calculating and the MATLAB mathematical modelling will give the same answer for evaluated x and graph.

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24

Siddiqui, Arsheen Neda. "Digital watermarking using MATLAB." Global Sci-Tech 10, no. 4 (2018): 242. http://dx.doi.org/10.5958/2455-7110.2018.00034.4.

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25

Szymczyk, Magdalena, and Piotr Szymczyk. "Matlab and Parallel Computing." Image Processing & Communications 17, no. 4 (December 1, 2012): 207–16. http://dx.doi.org/10.2478/v10248-012-0048-5.

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Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.

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26

Dunn, Peter K., and Chris Harman. "Calculus demonstrations using MATLAB." International Journal of Mathematical Education in Science and Technology 33, no. 4 (July 2002): 584–96. http://dx.doi.org/10.1080/002073902320300856.

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27

Funt, Brian. "Retinex in MATLAB™." Journal of Electronic Imaging 13, no. 1 (January 1, 2004): 48. http://dx.doi.org/10.1117/1.1636761.

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28

Kurasov, D. "Mathematical modeling system MatLab." Journal of Physics: Conference Series 1691 (November 2020): 012123. http://dx.doi.org/10.1088/1742-6596/1691/1/012123.

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29

Nkwocha, Fidel, and Sebastian Elbaum. "Fault patterns in Matlab." ACM SIGSOFT Software Engineering Notes 30, no. 4 (July 2005): 1–4. http://dx.doi.org/10.1145/1082983.1083235.

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30

Kovarik, Martin, and Petr Klimek. "Cluster Analysis in MATLAB." Informační Bulletin České statistické společnosti 22, no. 1 (2011): 20–27. http://dx.doi.org/10.5300/ib/2011-1/20.

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31

Moler, Cleve, and Jack Little. "A history of MATLAB." Proceedings of the ACM on Programming Languages 4, HOPL (June 12, 2020): 1–67. http://dx.doi.org/10.1145/3386331.

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32

Travinin Bliss, N., and J. Kepner. "'pMATLAB Parallel MATLAB Library'." International Journal of High Performance Computing Applications 21, no. 3 (August 2007): 336–59. http://dx.doi.org/10.1177/1094342007078446.

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33

Luszczek, Piotr. "Parallel Programming in MATLAB." International Journal of High Performance Computing Applications 23, no. 3 (June 16, 2009): 277–83. http://dx.doi.org/10.1177/1094342009106194.

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A visit to the neighborhood PC retail store provides ample proof that we are in the multi-core era. The key differentiator among manufacturers today is the number of cores that they pack onto a single chip. The clock frequency of commodity processors has reached its limit, however, and is likely to stay below 4 GHz for years to come. As a result, adding cores is not synonymous with increasing computational power. To take full advantage of the performance enhancements offered by the new multi-core hardware, a corresponding shift must take place in the software infrastructure — a shift to parallel computing.

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34

Shampine, L. F., and S. Thompson. "Solving DDEs in Matlab." Applied Numerical Mathematics 37, no. 4 (June 2001): 441–58. http://dx.doi.org/10.1016/s0168-9274(00)00055-6.

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35

Gautschi, Walter. "Orthogonal polynomials (in Matlab)." Journal of Computational and Applied Mathematics 178, no. 1-2 (June 2005): 215–34. http://dx.doi.org/10.1016/j.cam.2004.03.029.

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36

Shacham, Mordechai. "Scientific Computing with MATLAB." Computer Physics Communications 161, no. 3 (August 2004): 183–85. http://dx.doi.org/10.1016/j.cpc.2004.02.017.

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37

Sobie, E. A. "An Introduction to MATLAB." Science Signaling 4, no. 191 (September 13, 2011): tr7. http://dx.doi.org/10.1126/scisignal.2001984.

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38

Kathrani, Kunal, Piyush Agrawal, and Khushi Khanchandani. "CAPTCHA Cracker using MATLAB." International Journal of Computer Applications 139, no. 13 (April 15, 2016): 20–23. http://dx.doi.org/10.5120/ijca2016909531.

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39

Paramesh, G., K. V. Pavithra, N. Ranjitha, S. Swetha, and T. Anushalalitha. "Video Steganography using MATLAB." EAI Endorsed Transactions on Cloud Systems 3, no. 10 (December 20, 2017): 153493. http://dx.doi.org/10.4108/eai.20-12-2017.153493.

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40

Sayood, Khalid. "Learning Programming Using MATLAB." Synthesis Lectures on Electrical Engineering 1, no. 1 (January 2006): 1–88. http://dx.doi.org/10.2200/s00051ed1v01y200609eel003.

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41

Alexandrov, Albert, Yuri Orlov, and Liubov Mikhaylova. "Package “Automatica” for MATLAB*." IFAC Proceedings Volumes 45, no. 16 (July 2012): 1832–37. http://dx.doi.org/10.3182/20120711-3-be-2027.00043.

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42

Doherty, Jesse, Laurie Hendren, and Soroush Radpour. "Kind analysis for MATLAB." ACM SIGPLAN Notices 46, no. 10 (October 18, 2011): 99–118. http://dx.doi.org/10.1145/2076021.2048077.

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43

Luo, Jiao Yan, and Xiang E. Sun. "Matlab-Based Formant Estimation." Applied Mechanics and Materials 577 (July 2014): 798–801. http://dx.doi.org/10.4028/www.scientific.net/amm.577.798.

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In the study of speech digital signal processing, the resonance peak is the major characteristics in reflecting track resonant. In order to be more conducive to the future development of speech signal processing techniques, three methods of the formant estimation are introduced in the article, namely, Short-time Fourier Transform method, Cepstrum, LPC estimation method. These methods are compared and analyzed by means of MATLAB programming, and it is concluded that LPC method is the best method, which can estimate the formant peaks more accurate.

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44

Shampine, Lawrence F., and Mark W. Reichelt. "The MATLAB ODE Suite." SIAM Journal on Scientific Computing 18, no. 1 (January 1997): 1–22. http://dx.doi.org/10.1137/s1064827594276424.

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45

Wellock, C., V. Chickarmane, and H. M. Sauro. "The SBW-MATLAB interface." Bioinformatics 21, no. 6 (November 5, 2004): 823–24. http://dx.doi.org/10.1093/bioinformatics/bti110.

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46

Syffen, Georgette, Ahmed Khalil, and Ibrahim Ramadan. "ORIGINDESTINATIONMATRIXESTIMATIONBASEDONTRAFFICCOUNTSUSINGFMINCON FUNCTION IN MATLAB." Journal of Al-Azhar University Engineering Sector 18, no. 66 (January 1, 2023): 57–73. http://dx.doi.org/10.21608/auej.2023.283020.

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47

Tian, Daquan, Soroosh Sorooshian, and Donald E. Myers. "Correspondence analysis with Matlab." Computers & Geosciences 19, no. 7 (August 1993): 1007–22. http://dx.doi.org/10.1016/0098-3004(93)90006-q.

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48

Rich, Lawrence C., and David R. Hill. "Automatic differentiation in MATLAB." Applied Numerical Mathematics 9, no. 1 (January 1992): 33–43. http://dx.doi.org/10.1016/0168-9274(92)90065-l.

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49

Wessel, Paul, and Joaquim F. Luis. "The GMT/MATLAB Toolbox." Geochemistry, Geophysics, Geosystems 18, no. 2 (February 2017): 811–23. http://dx.doi.org/10.1002/2016gc006723.

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50

Otto, Steve. "MATLAB Guide MATLAB Guide by Desmond J Higham & Nicholas J Higham." MSOR Connections 1, no. 1 (February 2001): 16. http://dx.doi.org/10.11120/msor.2001.01010016.

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