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

coagulate

Naoto Kaio,Tadashi Dohi,Shunji Osaki abelian groups. It is, therefore, natural to introduce ., which are maps between chain complexes. This notion permits us to compare different chain complexes in the same fashion that homomorphisms allow us to compare abelian groups. A homomorphism of abelian groups is required to preserve group add

nostrum

Gyrate

Chengjie Wang,Qingpei Hu,Dan Yuus and dimension-independent manner. We begin with the introduction of representable sets. These are sets that can be constructed using elementary cells and represent a larger class than that of cubical sets. This extra flexibility is used in Section 6.2 to construct cubical multivalued maps. As des

Commonwealth

Consecutive , and Related Models—A Surveye discuss the image of the Sea of Tranquillity (see Figure 1.5). However, such a complicated image and the discussion surrounding it can mask some of the even more elementary difficulties in the process of analog to digital conversion. Since the focus of this book is on computational homology, we wi

Flavouring

,Approximations for “Long-Lived” Particles,f components of . that are disjoint from .. Using this as motivation, in Section 9.1 we introduce the concept of relative homology. Though motivated by a simple problem, it turns out that relative homology is an extremely powerful tool, both as a means of extracting topology from the homological alg

使迷醉

Contort

Vladimir S. Korolyuk,Vladimir V. Korolyukand 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 wi

狼群

Probability and Information Theory,ramming language, because we do not want to delve too deeply into the technicalities involved in preparing a concrete computer program. The langauge we use is a combination of features found in present-day programming languages which we feel are most useful to keep the presentation reasonably detail

Cognizance

Textbook 2004uses a computer to develop a combinatorial computational approach to the subject. The core of the book deals with homology theory and its computation. Following this is a section containing extensions to further developments in algebraic topology, applications to computational dynamics, and applicat

腐烂

On Stochastic Coherent Systems,an be computed efficiently, and how homology provides us with information about the geometry and topology of nonlinear objects and functions. Given the amount of theory that needs to be developed, it is easy to lose sight of these objectives along the way.