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Automatic Differentiation Introductions Automatic Differentiation What is Automatic Differentiation? Algorithmic, or automatic, differentiation (AD) is concerned with the accurate and efficient evaluation of derivatives for functions defined by computer programs. No truncation errors are incurred, and the resulting numerical derivative
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Introduction to Numerical Differentiation Approximating a Derivative (Cont’d) To approximate f′(x0), suppose first that x0 (a,b), where f C2[a,b], and that x1 x0 h for some h 6 0 that is sufficiently small to ensure that x1 [a,b]. Numerical Analysis (Chapter 4) Numerical Diff
theory of four aspects: differentiation, functionalization, added value, and empathy. The purpose of differentiation is a strategy to distinguish oneself from competitors through technology or services, etc. It is mainly divided into three aspects: market differentiation, product differentiation and image differentiation.
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Categories and Subject Descriptors: G.1.4 [Numerical Analysis]: Automatic Differentiation General Terms: Automatic Differentiation, Numerical Methods, MATLAB Additional Key Words and Phrases: algorithmic differentiation, scientific computation, applied mathemat-ics, chain rule, forward mode, overloading, source transformation ACM Reference Format:
1.5.1 Differentiation strategy 5 1.5.2 Service differentiation 5 1.5.3 Competitive advantage 5 1.5.4 Human capital resource 6 1.5.5 Customer relations 6 1.6 Disposition 6 2 theory8 2.1 Marketing strategies 8 2.1.1 Categorizing generic strategies 9 2.1.2 Differentiation strategy 9 2.1.3 Service differentiation strategy 10 2.2 Resource-based view 10