Relevant bibliographies by topics / Mathematical and symbolic

Contents

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

Academic literature on the topic 'Mathematical and symbolic'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Mathematical and symbolic"

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Wolfram, Stephen. "Symbolic mathematical computation." Communications of the ACM 28, no. 4 (April 1985): 390–94. http://dx.doi.org/10.1145/3341.3347.

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Bing, Thomas J., and Edward F. Redish. "Symbolic manipulators affect mathematical mindsets." American Journal of Physics 76, no. 4 (April 2008): 418–24. http://dx.doi.org/10.1119/1.2835053.

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Lutovac, Miroslav, and Dejan Tosic. "Symbolic signal processing and system analysis." Facta universitatis - series: Electronics and Energetics 16, no. 3 (2003): 423–31. http://dx.doi.org/10.2298/fuee0303423l.

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We present new software in MATLAB and Mathematica for symbolic signal processing and system analysis. Our mission is to encapsulate high-tech engineering and sophisticated mathematical knowledge into easy-to-use software that effectively solves practical problems.
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Vasileva, Natalia, Vladimir Grigorev-Golubev, and Irina Evgrafova. "Mathematical programming in Mathcad and Mathematica." E3S Web of Conferences 419 (2023): 02007. http://dx.doi.org/10.1051/e3sconf/202341902007.

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An article generalizes the long-term work of authors with packages of applied mathematical programs. It discusses and demonstrates the features and methods of solution of mathematical tasks in mathematical package Mathcad and Mathematica: from the simplest ones, included in the set of typical problems of mathematical disciplines for training specialists for shipbuilding, to complex computational tasks and applied problems of professional orientation, which require the construction of a mathematical model and analysis of the results obtained. The examples show the solution of mathematical problems in symbolic form, mathematical studies in the Mathcad and Mathematica environment, and mathematical programming with these packages.
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Behmanesh-Fard, Navid, Hossein Yazdanjouei, Mohammad Shokouhifar, and Frank Werner. "Mathematical Circuit Root Simplification Using an Ensemble Heuristic–Metaheuristic Algorithm." Mathematics 11, no. 6 (March 19, 2023): 1498. http://dx.doi.org/10.3390/math11061498.

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Symbolic pole/zero analysis is a crucial step in designing an analog operational amplifier. Generally, a simplified symbolic analysis of analog circuits suffers from NP-hardness, i.e., an exponential growth of the number of symbolic terms of the transfer function with the circuit size. This study presents a mathematical model combined with a heuristic–metaheuristic solution method for symbolic pole/zero simplification in operational transconductance amplifiers. First, the circuit is symbolically solved and an improved root splitting method is applied to extract symbolic poles/zeroes from the exact expanded transfer function. Then, a hybrid algorithm based on heuristic information and a metaheuristic technique using simulated annealing is used for the simplification of the derived symbolic roots. The developed method is tested on three operational transconductance amplifiers. The obtained results show the effectiveness of the proposed method in achieving accurate simplified symbolic pole/zero expressions with the least complexity.
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Zhanatauov, S. U. "VERBAL, SYMBOLIC, MATHEMATICAL, SEMANTIC, BEHAVIORAL, COGNITIVE MODELS." Theoretical & Applied Science 113, no. 09 (September 30, 2022): 169–74. http://dx.doi.org/10.15863/tas.2022.09.113.32.

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Diez, F., and R. Moriyon. "Solving mathematical exercises that involve symbolic computations." Computing in Science & Engineering 6, no. 1 (January 2004): 81–84. http://dx.doi.org/10.1109/mcise.2004.1255826.

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Torresi, Sandra. "Interaction between domain-specific and domain-general abilities in math´s competence." Journal of Applied Cognitive Neuroscience 1, no. 1 (December 7, 2020): 43–51. http://dx.doi.org/10.17981/jacn.1.1.2020.08.

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This article is an approach to some viewpoints about interactions between domain-specific and general cognitive tools involved in the development of mathematical competence. Many studies report positive correlations between the acuity of the numerical approximation system and formal mathematical performance, while another important group of investigations have found no evidence of a direct connection between non-symbolic and symbolic numerical representations. The challenge for future research will be to focus on correlations and possible causalities between non-symbolic and symbolic arithmetic skills and general domain cognitive skills in order to identify stable precursors of mathematical competence.
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Xu, Chang, Feng Gu, Katherine Newman, and Jo-Anne LeFevre. "The hierarchical symbol integration model of individual differences in mathematical skill." Journal of Numerical Cognition 5, no. 3 (December 20, 2019): 262–82. http://dx.doi.org/10.5964/jnc.v5i3.140.

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Symbolic number knowledge is strongly related to mathematical performance for both children and adults. We present a model of symbolic number relations in which increasing skill is a function of hierarchical integration of symbolic associations. We tested the model by contrasting the performance of two groups of adults. One group was educated in China (n = 71) and had substantially higher levels of mathematical skill compared to the other group who was educated in Canada (n = 68). Both groups completed a variety of symbolic number tasks, including measures of cardinal number knowledge (number comparisons), ordinal number knowledge (ordinal judgments) and arithmetic fluency, as well as other mathematical measures, including number line estimation, fraction/algebra arithmetic and word problem solving. We hypothesized that Chinese-educated individuals, whose mathematical experiences include a strong emphasis on acquiring fluent access to symbolic associations among numbers, would show more integrated number symbol knowledge compared to Canadian-educated individuals. Multi-group path analysis supported the hierarchical symbol integration hypothesis. We discuss the implications of these results for understanding why performance on simple number processing tasks is persistently related to measures of mathematical performance that also involve more complex and varied numerical skills.
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Lestari, Nurcholif Diah Sri, Wasilatul Murtafiah, Marheny Lukitasari, Suwarno Suwarno, and Inge Wiliandani Setya Putri. "IDENTIFIKASI RAGAM DAN LEVEL KEMAMPUAN REPRESENTASI PADA DESAIN MASALAH LITERASI MATEMATIS DARI MAHASISWA CALON GURU." KadikmA 13, no. 1 (April 30, 2022): 11. http://dx.doi.org/10.19184/kdma.v13i1.31538.

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Representation is one of the fundamental abilities of mathematics reflected by students understanding of mathematics concepts, principles, or procedures, so it becomes crucial for teachers to develop students' mathematical representation skills. This research was time to describe the representation used in the problem and the level of mathematical representation ability needed to solve mathematical literacy problems. The data was collected through the assignment to design mathematical literacy problems between 3-10 pieces and interview as triangulation on 35 prospective elementary school teacher students. The data are grouped based on various representations and analyzed quantitatively and descriptively. Then one problem is chosen randomly for each type of representation to describe the level of representation ability needed to solve the problem qualitatively. The results show that the mathematical representations used in designed mathematical literacy problems are pictorial-verbal, pictorial-symbolic, verbal-symbolic, pictorial, verbal, symbolic, and pictorial-verbal-symbolic representations. The level of representational ability that tends to be needed to solve problems is levels 0 and 1. This study suggests that prospective teacher students should develop mathematical representation knowledge to improve the quality of their learning in the future
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Dissertations / Theses on the topic "Mathematical and symbolic"

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Redelinghuys, Gideon. "Symbolic string execution." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/20335.

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Thesis (MSc)--Stellenbosch University, 2012.
ENGLISH ABSTRACT: Symbolic execution is a well-established technique for automated test generation and for nding errors in complex code. Most of the focus has however been on programs that manipulate integers, booleans, and even, references in object-oriented programs. Recently researchers have started looking at programs that do lots of string processing, motivated, in part, by the popularity of the web and the risk that errors in web servers may lead to security violations. Attempts to extend symbolic execution to the domain of strings are mainly divided into one of two camps: automata-based approaches and approaches based on bitvector analysis. Here we investigate these two approaches in a uni ed setting, namely the symbolic execution framework of Java PathFinder. We describe the implementations of both approaches and then do an evaluation to show under what circumstances each approach performs well (or not so well). We also illustrate the usefulness of the symbolic execution of strings by nding errors in real-world examples.
AFRIKAANSE OPSOMMING: Simboliese uitvoering is 'n bekende tegniek vir automatiese genereering van toetse en om foute te vind in ingewikkelde bronkode. Die fokus sover was grotendeels op programme wat gebruik maak van heelgetalle, boolse waardes en selfs verwysings in objek geörienteerde programme. Navorsers het onlangs begin kyk na programme wat baie gebruik maak van string prosessering, deelteliks gemotiveerd deur die populariteit van die web en die gepaardgaande risiko's daarvan. Vorige implementasies van simboliese string uitvoering word binne twee kampe verdeel: die automata gebaseerde benadering en bitvektoor gebaseerde benadering. Binne hierdie tesis word die twee benaderings onder een dak gebring, naamliks Java PathFinder. Die implentasie van beide benaderings word bespreek en ge-evalueer om die omstandighede uit te wys waarbinne elk beter sou vaar. Die nut van simboliese string uitvoering word geïllustreer deur dit toe te pas in foutiewe regte wêreld voorbeelde.
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Bishop, Joyce Wolfer Otto Albert D. Lubinski Cheryl Ann. "Middle school students' understanding of mathematical patterns and their symbolic representations." Normal, Ill. Illinois State University, 1997. http://wwwlib.umi.com/cr/ilstu/fullcit?p9803721.

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Thesis (Ph. D.)--Illinois State University, 1997.
Title from title page screen, viewed June 1, 2006. Dissertation Committee: Albert D. Otto, Cheryl A. Lubinski (co-chairs), John A. Dossey, Cynthia W. Langrall, George Padavil. Includes bibliographical references (leaves 119-123) and abstract. Also available in print.
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Uwimbabazi, Aline. "Extended probabilistic symbolic execution." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85804.

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Thesis (MSc)--Stellenbosch University, 2013.
ENGLISH ABSTRACT: Probabilistic symbolic execution is a new approach that extends the normal symbolic execution with probability calculations. This approach combines symbolic execution and model counting to estimate the number of input values that would satisfy a given path condition, and thus is able to calculate the execution probability of a path. The focus has been on programs that manipulate primitive types such as linear integer arithmetic in object-oriented programming languages such as Java. In this thesis, we extend probabilistic symbolic execution to handle data structures, thus allowing support for reference types. Two techniques are proposed to calculate the probability of an execution when the programs have structures as inputs: an approximate approach that assumes probabilities for certain choices stay fixed during the execution and an accurate technique based on counting valid structures. We evaluate these approaches on an example of a Binary Search Tree and compare it to the classic approach which only take symbolic values as input.
AFRIKAANSE OPSOMMING: Probabilistiese simboliese uitvoering is ’n nuwe benadering wat die normale simboliese uitvoering uitbrei deur waarksynlikheidsberekeninge by te voeg. Hierdie benadering kombineer simboliese uitvoering en modeltellings om die aantal invoerwaardes wat ’n gegewe padvoorwaarde sal bevredig, te beraam en is dus in staat om die uitvoeringswaarskynlikheid van ’n pad te bereken. Tot dus vêr was die fokus op programme wat primitiewe datatipes manipuleer, byvoorbeeld lineêre heelgetalrekenkunde in objek-geörienteerde tale soos Java. In hierdie tesis brei ons probabilistiese simboliese uitvoering uit om datastrukture, en dus verwysingstipes, te dek. Twee tegnieke word voorgestel om die uitvoeringswaarskynlikheid van ’n program met datastrukture as invoer te bereken. Eerstens is daar die benaderingstegniek wat aanneem dat waarskynlikhede vir sekere keuses onveranderd sal bly tydens die uitvoering van die program. Tweedens is daar die akkurate tegniek wat gebaseer is op die telling van geldige datastrukture. Ons evalueer hierdie benaderings op ’n voorbeeld van ’n binêre soekboom en vergelyk dit met die klassieke tegniek wat slegs simboliese waardes as invoer neem.
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Lindroth, Olof. "A random formula lower bound for ordered DLL extended with local symmetry recognition /." Uppsala, 2004. http://www.math.uu.se/research/pub/Lindroth1.pdf.

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Lindman, Phillip A. (Phillip Anthony). "Intuition versus Formalization: Some Implications of Incompleteness on Mathematical Thought." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc277970/.

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This paper describes the tension between intuition about number theory and attempts to formalize it. I will first examine the root of the dilemma, Godel's First Incompleteness Theorem, which demonstrates that in any reasonable formalization of number theory, there will be independent statements. After proving the theorem, I consider some of its consequences on intuition, focusing on Freiling's "Dart Experiment" which is based on our usual notion of the real numbers as a line. This experiment gives an apparent refutation of the Axiom of Choice and the Continuum Hypothesis; however, it also leads to an equally apparent paradox. I conclude that such paradoxes are inevitable as the formalization of mathematics takes us further from our initial intuitions.
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Gorman, Judith A. "Aspects of coherent logic." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=63868.

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Brierley, William. "Undecidability of intuitionistic theories." Thesis, McGill University, 1985. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66016.

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Lindberg, Maja. "The innate ability to cope with mathematics : A comparative fMRI study of children's and adults' neural activity during non-symbolic mathematical tasks." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158199.

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Humans as well as animals are born with a number sense, an innate ability to make approximations (Dehaene, 1997). However, low numeracy is an issue today and have a larger impact on the individuals lives than poor reading abilities (Parsons & Bynner, 2006). To be able to understand the cause of developmental dyscalculia the fully functional brain coping with numbers must be further investigated. The aim of this study is hence to examine how the number sense develop during maturation. Seven children and seven adults (all healthy) have participated in this neuro imaging study. The participants were required to perform a non-symbolic mathematic task and a control task both outside and within the scanner. The results indicate a transition of active areas in the brain during maturation. In the children prefrontal areas were recruited, and for the adults the activation was primarily found in the parietal cortex. These findings, despite low statistical power indicates a shift of neural activity from a more cognitive demanding task into an automated task. Further studies will have to replicate the experiment to validate the findings of this study.
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Wheeler, Russell Clark. "Using symbolic dynamical systems: A search for knot invariants." CSUSB ScholarWorks, 1998. https://scholarworks.lib.csusb.edu/etd-project/3033.

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Sharma, Richa. "Semi-automated approach to support logical formalism for requirements analysis and validation." Thesis, IIT Delhi, 2016. http://localhost:8080/xmlui/handle/12345678/7227.

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Books on the topic "Mathematical and symbolic"

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Understanding symbolic logic. 2nd ed. Englewood Cliffs, N.J: Prentice Hall, 1989.

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Klenk, Virginia. Understanding symbolic logic. 3rd ed. Upper Saddle River, N.J: Prentice Hall, 1994.

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Klenk, Virginia. Understanding symbolic logic. 3rd ed. Englewood Cliffs, N.J: Prentice Hall, 1994.

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Understanding symbolic logic. New York: Custom Publishing, a division of Pearson, 2008.

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Smith, Karl J. Introduction to symbolic logic. 2nd ed. Pacific Grove, Calif: Brooks/Cole Pub. Co., 1991.

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Symbolic logic. Australia: Wadsworth/Thomson Learning, 2001.

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1915-, Metropolis N., ed. Symbolic dynamics of trapezoidal maps. Dordrecht: D. Reidel Pub. Co., 1986.

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Peter, Milosav, and Ercegovaca Irene, eds. Mathematics and mathematical logic: New research. Hauppauge, NY: Nova Science Publishers, 2009.

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Klenk, Virginia. Understanding symbolic logic. 2nd ed. Englewood Cliffs, N.J: Prentice Hall, 1989.

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Martin, Robert M. Introducing symbolic logic. Peterborough, Ont: Broadview Press, 2004.

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Book chapters on the topic "Mathematical and symbolic"

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Awange, Joseph L., Béla Paláncz, Robert H. Lewis, and Lajos Völgyesi. "Symbolic Regression." In Mathematical Geosciences, 321–57. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-67371-4_11.

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Awange, Joseph L., Béla Paláncz, Robert H. Lewis, and Lajos Völgyesi. "Symbolic Regression." In Mathematical Geosciences, 433–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-92495-9_12.

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Glasner, Eli. "Symbolic representations." In Mathematical Surveys and Monographs, 269–97. Providence, Rhode Island: American Mathematical Society, 2003. http://dx.doi.org/10.1090/surv/101/15.

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Gilmore, Camilla, Silke M. Göbel, and Matthew Inglis. "Symbolic Number." In An Introduction to Mathematical Cognition, 29–50. Matthew Inglis. Description: Abingdon, Oxon ; New York, NY : Routledge, 2018. |: Routledge, 2018. http://dx.doi.org/10.4324/9781315684758-3.

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Cohen, Arjeh M. "Interactive Mathematical Documents." In Artificial Intelligence and Symbolic Computation, 1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11856290_1.

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Wang, Paul S. "Modern Symbolic Mathematical Computation Systems." In Applications of Computer Algebra, 62–73. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4684-6888-5_2.

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Mazzucco, Isolde. "SYMOPT: Symbolic Parametric Mathematical Programming." In Computer Algebra in Scientific Computing CASC 2001, 417–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56666-0_32.

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Kohlhase, Michael, and Ioan Sucan. "A Search Engine for Mathematical Formulae." In Artificial Intelligence and Symbolic Computation, 241–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11856290_21.

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Pfalzgraf, J. "On mathematical modeling in robotics." In Artificial Intelligence and Symbolic Mathematical Computing, 116–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57322-4_8.

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Diveev, Askhat, and Elizaveta Shmalko. "Mathematical Statements of MLC Problems." In Machine Learning Control by Symbolic Regression, 7–25. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-83213-1_2.

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Conference papers on the topic "Mathematical and symbolic"

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Watt, Stephen M. "On the Mathematics of Mathematical Handwriting Recognition." In 12th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2010). IEEE, 2010. http://dx.doi.org/10.1109/synasc.2010.93.

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Ludwig, Simone A., Omer F. Rana, William Naylor, and Julian Padget. "Mathematical matchmaker for numeric and symbolic services." In the fourth international joint conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1082473.1082819.

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Buchberger, Bruno. "Mathematical Theory Exploration." In 2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. IEEE, 2006. http://dx.doi.org/10.1109/synasc.2006.50.

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Sasaki, Yuji, Keito Tanemura, Yuki Tokuni, Ryohei Miyadera, and Hikaru Manabe. "Application of Symbolic Regression to Unsolved Mathematical Problems." In 2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1). IEEE, 2023. http://dx.doi.org/10.1109/icaia57370.2023.10169711.

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Kasihmuddin, Mohd Shareduwan Mohd, Saratha Sathasivam, and Mohd Asyraf Mansor. "Artificial bee colony in neuro - Symbolic integration." In PROCEEDINGS OF THE 24TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Mathematical Sciences Exploration for the Universal Preservation. Author(s), 2017. http://dx.doi.org/10.1063/1.4995912.

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Mansor, Mohd Asyraf, and Saratha Sathasivam. "Activation function comparison in neural-symbolic integration." In ADVANCES IN INDUSTRIAL AND APPLIED MATHEMATICS: Proceedings of 23rd Malaysian National Symposium of Mathematical Sciences (SKSM23). Author(s), 2016. http://dx.doi.org/10.1063/1.4954526.

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Watt, Stephen. "Improving Pen-Based Mathematical Interfaces." In 2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. IEEE, 2006. http://dx.doi.org/10.1109/synasc.2006.46.

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Carstea, Alexandru, Georgiana Macariu, Marc Frincu, and Dana Petcu. "Composing Web-Based Mathematical Services." In 2007 Ninth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. IEEE, 2007. http://dx.doi.org/10.1109/synasc.2007.39.

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Larcombe, P. J. "Exact algebraic pole-zero cancellation using symbolic mathematical computation." In UKACC International Conference on Control (CONTROL '98). IEE, 1998. http://dx.doi.org/10.1049/cp:19980212.

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DOS REIS, G., B. MOURRAIN, PH TRÉBUCHET, and F. ROUILLIER. "AN ENVIRONMENT FOR SYMBOLIC AND NUMERIC COMPUTATION." In Proceedings of the First International Congress of Mathematical Software. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812777171_0024.

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Reports on the topic "Mathematical and symbolic"

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Steinberg, Stanly. Symbol Manipulation and Applied Mathematics. Fort Belvoir, VA: Defense Technical Information Center, March 1986. http://dx.doi.org/10.21236/ada179571.

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