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Sprawdź 19 najlepszych książek naukowych na temat „Generalized Metric Spaces”.

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1

Lin, Shou, and Ziqiu Yun. Generalized Metric Spaces and Mappings. Atlantis Press, 2016. http://dx.doi.org/10.2991/978-94-6239-216-8.

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2

Karapinar, Erdal, and Ravi P. Agarwal. Fixed Point Theory in Generalized Metric Spaces. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14969-6.

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Abate, Marco. Finsler metrics-- a global approach: With applications to geometric function theory. Springer-Verlag, 1994.

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Lin, Shou, and Ziqiu Yun. Generalized Metric Spaces and Mappings. Atlantis Press (Zeger Karssen), 2016.

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Karapinar, Erdal, and Ravi P. Agarwal. Fixed Point Theory in Generalized Metric Spaces. Springer International Publishing AG, 2022.

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Fixed Point Theory in Generalized Metric Spaces. Springer International Publishing AG, 2023.

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7

Fundamentals of Signal Processing in Generalized Metric Spaces. CRC Press LLC, 2022.

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8

Busemann, Herbert. Metric Methods of Finsler Spaces and in the Foundations of Geometry. (AM-8). Princeton University Press, 2016.

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9

Popoff, Andrey. Fundamentals of Signal Processing in Generalized Metric Spaces: Algorithms and Applications. Taylor & Francis Group, 2022.

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Popoff, Andrey. Fundamentals of Signal Processing in Generalized Metric Spaces: Algorithms and Applications. Taylor & Francis Group, 2022.

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11

Popoff, Andrey. Fundamentals of Signal Processing in Generalized Metric Spaces: Algorithms and Applications. Taylor & Francis Group, 2022.

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Fundamentals of Signal Processing in Generalized Metric Spaces: Algorithms and Applications. CRC Press LLC, 2022.

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13

Metrics on the phase space and non-selfadjoint pseudo-differential operators. Birkhäuser, 2010.

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14

Deruelle, Nathalie, and Jean-Philippe Uzan. Vector geometry. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198786399.003.0002.

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This chapter defines the mathematical spaces to which the geometrical quantities discussed in the previous chapter—scalars, vectors, and the metric—belong. Its goal is to go from the concept of a vector as an object whose components transform as Tⁱ → 𝓡ⱼ ⁱTj under a change of frame to the ‘intrinsic’ concept of a vector, T. These concepts are also generalized to ‘tensors’. The chapter also briefly remarks on how to deal with non-Cartesian coordinates. The velocity vector v is defined as a ‘free’ vector belonging to the vector space ε‎3 which subtends ε‎3. As such, it is not bound to the point P
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15

Theory of Complex Finsler Geometry and Geometry of Intrinsic Metrics. World Scientific Publishing Co Pte Ltd, 2016.

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16

Theory of Complex Finsler Geometry and Geometry of Intrinsic Metrics. World Scientific Publishing Co Pte Ltd, 2016.

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17

Tretkoff, Paula. Topological Invariants and Differential Geometry. Princeton University Press, 2017. http://dx.doi.org/10.23943/princeton/9780691144771.003.0002.

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This chapter deals with topological invariants and differential geometry. It first considers a topological space X for which singular homology and cohomology are defined, along with the Euler number e(X). The Euler number, also known as the Euler-Poincaré characteristic, is an important invariant of a topological space X. It generalizes the notion of the cardinality of a finite set. The chapter presents the simple formulas for computing the Euler-Poincaré characteristic (Euler number) of many of the spaces to be encountered throughout the book. It also discusses fundamental groups and covering
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18

Hrushovski, Ehud, and François Loeser. The space of stably dominated types. Princeton University Press, 2017. http://dx.doi.org/10.23943/princeton/9780691161686.003.0003.

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This chapter introduces the space unit vector V of stably dominated types on a definable set V. It first endows unit vector V with a canonical structure of a (strict) pro-definable set before providing some examples of stably dominated types. It then endows unit vector V with the structure of a definable topological space, and the properties of this definable topology are discussed. It also examines the canonical embedding of V in unit vector V as the set of simple points. An essential feature in the approach used in this chapter is the existence of a canonical extension for a definable functi
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19

Mercati, Flavio. York’s Solution to the Initial-Value Problem. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789475.003.0008.

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In this chapter I briefly review York’s method (or the conformal method) for solving the initial value problem of (GR). This method, developed initially by Lichnerowicz and then generalized by Choquet-Bruhat and York, allows to find solutions of the constraints of (GR) (in particular the Hamiltonian, or refoliation constraint) by scanning the conformal equivalence class of spatial metrics for a solution of the Hamiltonian constraint, exploiting the fact that, in a particular foliation (CMC), the transverse nature of the momentum field is preserved under conformal transformations. This method a
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