Relevant bibliographies by topics / MATLAB

Academic literature on the topic 'MATLAB'

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Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "MATLAB"

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

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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "MATLAB"

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Dubrau, Anton. "Taming Matlab." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=107702.

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MATLAB is a dynamic scientific language used by scientists, engineers and students worldwide. Although MATLAB is very suitable for rapid prototyping and development, MATLAB users often want to convert their final MATLAB programs to a static language such as FORTRAN, to integrate them into already existing programs of that language, to leverage the performance of powerful static compilers, or to ease the distribution of executables. This thesis presents an extensible object-oriented toolkit to help facilitate the generation of static programs from dynamic MATLAB programs. Our open source toolkit, called the MATLAB Tamer, targets a large subset of MATLAB. Given information about the entry point of the program, the MATLAB Tamer builds a complete callgraph, transforms every function into a reduced intermediate representation, and provides typing information to aid the generation of static code. In order to provide this functionality, we need to handle a large number of MATLAB builtin functions. Part of the Tamer framework is the builtin framework, an extensible toolkit which provides a principled approach to handle a large number of builtin functions. To build the callgraph, we provide an interprocedural analysis framework, which can be used to implement full-program analyses. Using this interprocedural framework, we have developed value analysis, an extensible interprocedural analysis to estimate MATLAB types, which helps discover the call edges needed to build the call graph. In order to make the static analyses even possible, we disallow a small number of MATLAB constructs and features, but attempt to support as large a subset of MATLAB as possible. Thus, by both slightly restricting MATLAB, and by providing a framework with powerful analyses and simplifying transformations, we can "Tame MATLAB".
MATLAB est un langage scientifique utilisé par des ingénieurs, scientifiques, et étudiants à travers le monde. Bien que MATLAB soit très approprié pour les prototypages et les développements rapides, les usagers veulent souvent convertir leurs programmes MATLAB finaux vers un langage statique tel FORTRAN, dans le but de les intégrer à des programmes existants dans ce langage, de tirer avantage des performances des compilateurs statiques plus puissants, ou de faciliter la distribution des fichiers exécutables. Cette thèse présente un toolkit extensible orienté objet pour faciliter la production de programmes statiques à partir de programmes MATLAB dynamiques. Notre toolkit à code source libre, appelé MATLAB Tamer («dompteur MATLAB »), vise un large sous-ensemble de MATLAB. À partir d'informations sur le point d'entrée du programme, le MATLAB Tamer construit un graphe d'appels complet, transforme chaque fonction en une représentation réduite intermédiaire et fournit l'information sur le typage pour faciliter la production du code statique. Pour fournir cette fonctionnalité, nous devons manipuler une grand nombre de fonctions MATLAB intégrées. Une partie du cadre du Tamer est le cadre intégré, un toolkit extensible fournissant une approche de principe pour manipuler un grand nombre de fonctions intégrées. Pour construire le graphe d'appels, nous fournissons un cadre d'analyse interprocédural pouvant être utilisé pour implanter des analyses de programmes complets. En utilisant ce cadre inter-procédural, nous avons développé l'analyse des valeurs, une analyse inter-procédurale extensible pour estimer les types MATLAB, pour aider à découvrir les arrêtes d'appels nécessaires pour construire le graphe d'appels. Pour pouvoir rendre faisable une analyse statique, nous interdisons un petit nombre de concepts et caractéristiques de MATLAB, mais nous tentons de supporter un sous-ensemble de MATLAB aussi grand que possible. Conséquemment, en restreignant légèrement MATLAB, en fournissant un puissant cadre d'analyse et en simplifiant les transformations, nous pouvons «dompter MATLAB».
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Elphick, Daniel R. "Partially evaluating MATLAB." Thesis, University of Southampton, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427430.

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Phillips, Donovan D. "Mathematical modeling using MATLAB." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA358796.

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Thesis (M.S. in Applied Mathematics) Naval Postgraduate School, December 1998.
"December 1998." Thesis advisor(s): Maurice D. Weir. Includes bibliographical references (p. 121). Also available online.
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Šeškutė, Kristina. "MATLAB vaizdinio programavimo galimybės." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2005. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050608_172428-46401.

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For the user’s comfort in modern programs are created system of means, which are called graphical user interface (GUI). GUI is the window, created by user, with lay out graphical elements: command push button, edit text, list boxes, checkboxes, menu and etc. User graphical interface technology started to implant also in modern computer systems, from which the most advanced one – MATLAB. This work examines two ways of MATLAB graphical user interface creation, looks over graphical elements, MATLAB visual possibilities are compared with one the most popular programming medium C++Builder. In applied example are presented the discrete-time signal examples and real sound “a” signal, witch is possible not even depict, but also to hear out. This example demonstrates graphical user interface created by MATLAB.
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Radpour, Soroush. "Understanding and refactoring MATLAB." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110652.

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Matlab is a very popular dynamic scripting language for numericalcomputations used by scientists, engineers and students world-wide. Matlabprograms are often developed incrementally using a mixture of Matlab scriptsand functions and frequently build upon existing code which may use outdatedfeatures. This results in programs that could benefit from refactoring,especially if the code will be reused and/or distributed. Despite the needfor refactoring there appear to be no Matlab refactoring tools available.Correct refactoring of Matlab is quite challenging because of itsnon-standard rules for binding identifiers. Even simple refactorings arenon-trivial. Compiler writers and software engineers are generally not familiar with \matlab and how it's used sothe problem has been left untouched so far. This thesis has two main contributions. The first is McBench, a tool that helps compiler writers understand the language better. In order to have a systematic approach to the problem, we developed this tool to give us some insight about how programmers use Matlab.The second contribution is a suite of semantic-preserving refactoring for Matlabfunctions and scripts including: function and script inlining, convertingscripts to functions, extracting new functions, and converting dynamic feval calls to static function calls. These refactorings have been implemented using the McLabcompiler framework, and an evaluation is given on a large set of Matlabprograms which demonstrates the effectiveness of our approach.
matlab est un langage de script dynamique utilisé à des fins de calcul numérique par des scientifiques, ingénieurs et étudiants du monde entier. Les programmes matlab sont souvent développés selon une méthode incrémentale, sur la base d'un mélange de scripts et fonctions Matlab, et sont habituellement conçus à partir d'un code existant dont les fonctionnalités seraient obsolètes. Par conséquent, certains programmes pourraient bénéficier de réusinage, surtout si le code sera réutilisé et/ou distribué. Malgré ce besoin, il n'existe aucun outil matlab de ce genre. Le réusinage de Matlab est assez difficile car les règles pour la liaison des identificateurs ne sont pas standards. Même une opération de maintenance simple revêt une certaine complexité. De plus, les créateurs de compilateurs et les ingénieurs en informatique ne sont généralement pas familiers avec matlab et la façon dont il est utilisé. C'est pourquoi à ce jour le problème n'a jamais été traité. Cette thèse apporte deux contributions principales: d'une part la création de MCBENCH, un outil aidant les créateurs de compilateurs à mieux comprendre le langage. Afin d'avoir une approche systématique du problème, nous avons développé cet outil pour en savoir plus sur la façon dont les programmeurs utilisent Matlab. L'autre contribution est une suite de réusinages préservant la sémantique des fonctions et scripts Matlab: incorporation de fonctions et scripts, conversion de scripts en fonctions, extraction de nouvelles fonctions et conversion d'appels dynamiques feval en appels de fonction statique. Le cadriciel et compilateur McLab a été utilisé pour la mise en œuvre de ces réusinages. De plus, une évaluation est donnée sur un large éventail de programmes Matlab afin de démontrer l'efficacité de notre approche.
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He, Xueming. "Integrating SciSPARQL and MATLAB." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-220907.

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Nowadays many scientific experiment results involve multi-dimensional arrays. It is desirable to store these results in a persistent way and make queries against not only well-structured data objects like arrays but also the metadata that describe the experiments. SPARQL is a Semantic Web standard query language for data and metadata stored in terms of RDF. SciSPARQL is an extended version of SPARQL designed for scientific applications. It includes numeric multi-dimensional array operations and user-defined functions. The SciSPARQL Database Manager (SSDM) is a query processing engine for SciSPARQL. MATLAB is a popular and powerful scientific computing application programming language. We implemented an interface between MATLAB and SciSPARQL called MATLAB SciSPARQL Link (MSL). MSL provides SciSPARQL queries in MATLAB through a client/server interface. It optionally also provides an interface to enable calls to MATLAB in SciSPARQL queries.  With MSL MATLAB users can populate, update, and query SSDM databases it in terms of SciSPARQL queries. For the implementation we use C interfaces of MATLAB and SSDM, and the networking capabilities of SSDM. The DLL we made extends MATLAB with MSL interface functions.
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Gu, Chenchen. "Option Pricing Using MATLAB." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/382.

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This paper describes methods for pricing European and American options. Monte Carlo simulation and control variates methods are employed to price call options. The binomial model is employed to price American put options. Using daily stock data I am able to compare the model price and market price and speculate as to the cause of difference. Lastly, I build a portfolio in an Interactive Brokers paper trading [1] account using the prices I calculate. This project was done a part of the masters capstone course Math 573: Computational Methods of Financial Mathematics.
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Välimäki, M. (Mauri). "Betonin suhteitus Matlab-ohjelmalla." Bachelor's thesis, University of Oulu, 2015. http://urn.fi/URN:NBN:fi:oulu-201506031766.

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Tässä työssä on keskitytty betonin suhteituksen laskemiseen lineaarisen regression kautta. Suhteitus on tärkeä betonin valmistuksen suunnitelma, jolla pyritään saamaan tuoreelle ja kovettuneella betonille halutut ominaisuudet. Puristuslujuus on betonin tärkein ominaisuus ja se toimii tässä työssä vastearvona. Puristuslujuuden vastearvoja tutkitaan ennustemuuttujien eli prediktorien avulla. Ennustemuuttujina ovat esimerkiksi sementtimäärä, vesimäärä, kiviainesmäärä ja erilaisten lisäaineiden määrä. Suhteitusta voidaan suorittaa reaaliaikaisesti betoniasemalla mutta mielestäni se tulisi ottaa yhdeksi suunnittelun osa-alueeksi. Tällöin on kuitenkin oltava betonissa reagoivien osa-aineiden käytöstä aikaisempaa tietoa, jonka avulla laskenta suoritetaan ja päätökset tehdään. Aineiston käsittelyä voidaan tehdä monellakin tavalla mutta nyt keskitytään lineaarisella regressiolla laskettaviin menetelmiin Matlab-ohjelmalla. Matlab-ohjelmassa on valmiina monia valmiita toimintoja laskennan suorittamiseksi ja tulosten esittämiseksi havainnollisesti
This work is focused on the concrete mix design calculation via linear regression. Concrete mix-design is important manufacturing plan, which aims to get desired properties into fresh and hardened concrete. Compressive strength of hardened concrete is the most important feature. Response values of concrete compressive strength are examined with predictors. Predictive variables are for example the amount of cement, water, aggregates and various additives. Concrete mix-design work can be performed in real-time in batching plant, but it should be taken as one action on normal design work. Before we can get any results and make decisions, we must have previous information about the behavior of the materials. The data processing can be done in many ways, but now we focus on the linear regression methods with a software Matlab. Matlab program has many ready-made functions and methods to perform calculations and present the results graphically
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Kumpula, O. (Ossi). "Puhujariippumaton automaattinen puheentunnistusjärjestelmä Matlab-ohjelmalla." Bachelor's thesis, University of Oulu, 2016. http://urn.fi/URN:NBN:fi:oulu-201611123027.

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Työn tarkoituksena oli tutustua automaattiseen puheentunnistukseen ja toteuttaa Matlab-ohjelmalla toimiva muutaman käskyn tunnistava puhujariippumaton puheentunnistusjärjestelmä, joka voidaan liittää simulaationukkeen kontrolloimaan sen hengitystä. Työssä tutustuttiin yleisiin ja järjestelmän toteutuksen kannalta merkittävimpiin puheentunnistuksen menetelmiin, joiden avulla puheentunnistusjärjestelmä rakennettiin. Toteutuksessa puhetta sisältävä signaali erotettiin hiljaisuudesta käyttäen Rabinerin ja Schaferin kuvaamaa algoritmia ja tunnistettavana yksikkönä käytettiin käskyt sisältävää fraasia. Piirreirrotus tehtiin Mel-Frequency Cepstrum Coefficients (MFCC) -menetelmällä ja akustiset mallit pohjautuivat Gaussin Mixture malliin (GMM) ja Markovin piilomalliin (HMM). Tunnistuksessa käytettiin useampaa mallia rinnakkain vähentämään satunnaisen puheen tunnistamista virheellisesti joksikin opetetuista käskyistä. Akustisten mallien harjoitteluun ja järjestelmän testaukseen tarvittava puheaineisto hankittiin pääasiassa Oulun yliopistollisen sairaalan Sädehoidon yksikön hoitajilta, jotka puheohjausjärjestelmää tulevat käyttämään. Testausten perusteella järjestelmä tunnisti alle 1 % virheellä oikeat puhekäskyt. Ongelmia tuli satunnaisen puheen virheellisellä tunnistuksella joksikin opetetuista puhekäskyistä, mitä ei onnistuttu kokonaan poistamaan. Järjestelmästä tuli kuitenkin toimiva käyttökohteeseensa, sillä käskyt annetaan painamalla näppäimistöstä enteriä pohjassa vastaavasti kuin potilaalle puhutaan mikrofonin kautta pitämällä tangenttia pohjassa ja nukelle annetaan pääsääntöisesti vain oikeita käskyjä
The aim of this thesis was to study automatic speech recognition (ASR) and produce Matlab-based speaker-independent ASR system that recognizes few speech commands and can be joined to control breathing of a simulation manikin. During this thesis commonly used ASR methods was studied and represented. In the produced ASR system, algorithm of Rabiner’s and Schafer’s was used to pick the speech signal from silence. Whole phrase containing the speech command was used as the recognition unit. Feature extraction was made by using Mel-Frequency Cepstrum Coefficients (MFCC) and acoustic models was based on Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM). During recognition state combine of the models was used in tandem to reduce the misrecognition of random speech as the speech commands. Set of speech signals for training the acoustic models and testing performance of the ASR system was acquired mainly in the Oulu University Hospital from nurses who will use the ASR system. The error ratio of the ASR system was less than 1 percent with the correct speech commands according to the tests. The main problem with the system was misrecognition of random speech as the speech commands. However, the ASR system is suitable for use because mainly only correct speech commands is spoken and the speech commands is spoken pressing and holding down the enter key
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Miškařík, Kamil. "Gramatická evoluce - Java/Matlab implementace." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-230931.

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Books on the topic "MATLAB"

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Rosenbaum, David A. MATLAB Blues. Abingdon, Oxon ; New York, NY : Routledge, [2020]: Routledge, 2019. http://dx.doi.org/10.4324/9780429299094.

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Turk, Irfan. Practical MATLAB. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5281-9.

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Paluszek, Michael, and Stephanie Thomas. MATLAB Recipes. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-0559-4.

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Gander, Walter. Learning MATLAB. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25327-5.

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Überhuber, Christoph, and Stefan Katzenbeisser. MATLAB 6.5. Vienna: Springer Vienna, 2002. http://dx.doi.org/10.1007/978-3-7091-6745-8.

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Überhuber, Christoph, and Stefan Katzenbeisser. MATLAB 6. Vienna: Springer Vienna, 2000. http://dx.doi.org/10.1007/978-3-7091-6780-9.

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Paluszek, Michael, and Stephanie Thomas. MATLAB Recipes. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6124-8.

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A, Davis Timothy, ed. MATLAB primer. 6th ed. Boca Raton: Chapman & Hall/CRC, 2002.

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Driscoll, Tobin A. Learning MATLAB. Philadelphia: Society for Industrial and Applied Mathematics, 2009.

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Coulson, Linda. MATLAB programming. Chandni Chowk, Delhi: Global Media, 2009.

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Book chapters on the topic "MATLAB"

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Benker, Hans. "MATLAB." In Ingenieurmathematik mit Computeralgebra-Systemen, 63–65. Wiesbaden: Vieweg+Teubner Verlag, 1998. http://dx.doi.org/10.1007/978-3-322-86587-8_10.

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Smith, Einar. "Matlab." In Introduction to the Tools of Scientific Computing, 193–218. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16972-4_9.

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Nowottny, Dietrich. "Matlab." In Mathematik am Computer, 25–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60222-1_3.

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Mustafy, Tanvir, and Md Tauhid Ur Rahman. "MATLAB." In Transactions on Computer Systems and Networks, 37–80. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-4661-7_2.

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Überhuber, Christoph, and Stefan Katzenbeisser. "Matlab." In MATLAB 6.5, 1–7. Vienna: Springer Vienna, 2002. http://dx.doi.org/10.1007/978-3-7091-6745-8_1.

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Überhuber, Christoph, and Stefan Katzenbeisser. "MATLAB." In MATLAB 6, 3–9. Vienna: Springer Vienna, 2000. http://dx.doi.org/10.1007/978-3-7091-6780-9_1.

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Smith, Einar. "MATLAB." In Introduction to the Tools of Scientific Computing, 185–210. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60808-8_9.

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Mishra, Shashi Kant, and Bhagwat Ram. "MATLAB." In Introduction to Linear Programming with MATLAB®, 21–44. Boca Raton : Taylor & Francis, CRC Press, 2018.: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315104003-3.

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Brito, Inês, Sofia Frade, and Radjon Haque. "Hello world: Programar estudos clássicos de psicologia com MATLAB." In Caderno de laboratório: Guia prático para investigadores/as. Iscte-Instituto Universitário de Lisboa, 2024. http://dx.doi.org/10.15847/lapsocadlab2024/matlab.

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Este capítulo visa: (a) Apresentar a plataforma MATLAB, como também, a sua aplicabilidade em investigação em Psicologia; (b) Apresentar noções básicas de MATLAB; (c) Demonstrar como ler um script de um estudo clássico de Psicologia; (d) Destacar recursos e suporte disponíveis tanto dentro da aplicação como online, de modo a auxiliar os utilizadores na programação e resolução de problemas.
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"MATLAB." In Fundamentals of Technical Mathematics, 271–87. Elsevier, 2016. http://dx.doi.org/10.1016/b978-0-12-801987-0.15002-6.

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Conference papers on the topic "MATLAB"

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Chipperfield, A. J. "The MATLAB Genetic Algorithm Toolbox." In IEE Colloquium on Applied Control Techniques Using MATLAB. IEE, 1995. http://dx.doi.org/10.1049/ic:19950061.

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Sorensen, O. B. "Kit software for use with MATLAB." In IEE Colloquium on Applied Control Techniques Using MATLAB. IEE, 1995. http://dx.doi.org/10.1049/ic:19950059.

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Margrave, F. "MATLAB - neural networks toolbox hardware post-processor." In IEE Colloquium on Applied Control Techniques Using MATLAB. IEE, 1995. http://dx.doi.org/10.1049/ic:19950057.

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Siqing Lu. "Power plant analyser - an applied Matlab toolbox." In IEE Colloquium on Applied Control Techniques Using MATLAB. IEE, 1995. http://dx.doi.org/10.1049/ic:19950062.

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Saifuddin, A. B. "Analysis of multivariable Smith predictors using MATLAB containers." In IEE Colloquium on Applied Control Techniques Using MATLAB. IEE, 1995. http://dx.doi.org/10.1049/ic:19950052.

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Alimi, M. H., M. Mahinfalah, and G. H. Nazari. "MATLAB in Engineering Education." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/cie-21277.

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Abstract:
Abstract One of the most important aspects of engineering education is problem solving. This paper intends to show how MATLAB can be utilized to solve various problems in science and engineering. A simple vibration problem is solved using MATLAB’s ODE solver to illustrate the excellent capability of MATLAB in numerical integration of matrix differential equations.
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Ivanov, S. "MATLAB-SIMULINK." In International Conference on Simulation (1998). IEE, 1998. http://dx.doi.org/10.1049/cp:19980637.

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Dubrau, Anton Willy, and Laurie Jane Hendren. "Taming MATLAB." In the ACM international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2384616.2384653.

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Whidborne, J. F. "MODCONS - a MATLAB toolbox for multi-objective control system design." In IEE Colloquium on Applied Control Techniques Using MATLAB. IEE, 1995. http://dx.doi.org/10.1049/ic:19950060.

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Maclay, D. "A controller and design implementation environment for the idle speed control of an internal combustion engine." In IEE Colloquium on Applied Control Techniques Using MATLAB. IEE, 1995. http://dx.doi.org/10.1049/ic:19950053.

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Reports on the topic "MATLAB"

1

Harvey, Dustin Yewell. MATLAB Reference. Office of Scientific and Technical Information (OSTI), June 2018. http://dx.doi.org/10.2172/1454948.

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Safranek, James. MATLAB-BASED LOCO. Office of Scientific and Technical Information (OSTI), August 2002. http://dx.doi.org/10.2172/800082.

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Snyder, Lawrence. Migrating MATLAB to ZPL. Fort Belvoir, VA: Defense Technical Information Center, October 2001. http://dx.doi.org/10.21236/ada398020.

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Terebilo, Andrei. Accelerator Toolbox for MATLAB. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/784910.

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Corbett, William. Interactive Orbit Control in MATLAB. Office of Scientific and Technical Information (OSTI), July 2001. http://dx.doi.org/10.2172/784990.

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Terebilo, Andrei. Channel Access Client Toolbox for Matlab. Office of Scientific and Technical Information (OSTI), August 2002. http://dx.doi.org/10.2172/799983.

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Terebilo, Andrei. Accelerator Modeling with MATLAB Accelerator Toolbox. Office of Scientific and Technical Information (OSTI), August 2002. http://dx.doi.org/10.2172/800064.

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Auman, Lamar M., and Jonathan Newby. A MATLAB/Aerodynamic Analyzer System Tool. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada412972.

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Wilson, D., Ross Alter, Katrina Burch, and Michelle Swearingen. Using EASEE’s acoustical calculations in MATLAB. Engineer Research and Development Center (U.S.), February 2019. http://dx.doi.org/10.21079/11681/32009.

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Martin, Grant D., and Armin Walter Doerry. SAR polar format implementation with MATLAB. Office of Scientific and Technical Information (OSTI), November 2005. http://dx.doi.org/10.2172/877139.

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