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Titlebook: Computational Homology; Tomasz Kaczynski,Konstantin Mischaikow,Marian Mroz Textbook 2004 Springer Science+Business Media New York 2004 Alg

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Computing Homology of MapsIn Chapter 6 we have provided a theoretical construction for producing a homology map .: .(.) → .(.) given an arbitrary continuous function . between cubical sets . ⊂ R. and . ⊂ R.. In this chapter we provide algorithms that allow us to use the computer to obtain ..
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Homology of Topological Polyhedraand 10, where we are required to work with large sets of data and for which we need a computationally effective means of computing homology. In all these examples the data itself naturally generates cubical sets. However, this cubical homology theory is unconventional, and furthermore, there is a wide variety of other homology theories available.
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https://doi.org/10.1007/978-3-540-24808-8d .(.) for some simple examples and discussed the method of elementary collapse, which can be used in special cases to compute these groups. In this chapter we want to go further and argue that the homology groups of any cubical set are computable. In fact, we will derive Algorithm 3.78, which, give
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