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Record W1967219124 · doi:10.1145/1504347.1504364

Unified formulas for arbitrary order symbolic derivatives and anti-derivatives of the power-inverse hyperbolic class 1

2009· article· en· W1967219124 on OpenAlexaff
Mhenni M. Benghorbal

Bibliographic record

VenueACM communications in computer algebra · 2009
Typearticle
Languageen
FieldMathematics
TopicFunctional Equations Stability Results
Canadian institutionsConcordia University
Fundersnot available
KeywordsMathematicsHyperbolic functionInverseOrder (exchange)Pure mathematicsInverse functionFunction (biology)Integer (computer science)Class (philosophy)Inverse trigonometric functionsDiscrete mathematicsCombinatoricsMathematical analysis

Abstract

fetched live from OpenAlex

We continue on tackling and giving a complete solution to the problem of finding the nth derivative and the nth anti-derivative, where n can be an integer, a fraction, a real, or a symbol, of elementary and special classes of functions. In general, the solutions are given through unified formulas in terms of the Fox H-function which in many cases can be simplified to less general functions. In this work, we consider two subclasses of the power-inverse hyperbolic class. Namely, the power-inverse hyperbolic sine class { f ( x ) : f ( x ) = Σ l j =1 Pj ( x α j )arcsinh(β j x γ j ), α j ∈ C, β j ∈ C\{0},γ j ∈ R\{0}, (1) and the power-inverse hyperbolic cosine class { f ( x ) : f ( x ) = Σ l j =1 Pj ( x α j )arccosh(β j x γ j ), α j ∈ C, β j ∈ C\{0},γ j ∈ R\{0}, (2) where pj's are polynomials of certain degrees. One of the key points in this work is that the approach does not depend on integration techniques The arbitrary order of differentiation is found according to the Riemann-Liouville definition, whereas the generalized Cauchy n-fold integral is adopted for arbitrary order of integration. The motivation of this work comes from the area of symbolic computation. The idea is that: Given a function f in a variable x , can CAS find a formula for the n th derivative, the n th anti-derivative, or both of f ? This enhances the power of integration and differentiation of CAS. In Maple, the formulas correspond to invoking the commands diff( f ( x ) for the n th derivative and int( f ( x ), x$n ) for the n th anti-derivative. A software exhibition will be given using Maple. Example: A unified formula for arcsinh(√ x ) in terms of the Meijer G-function (arcsinh(√ x )) (n) = x (1/2-- n over2√π G 1,2 over 1,2 (1/2,1/2over0, n --1/2│ x ) , │ x │ < 1. (3). The above G-function reduces to the original function if n = 0. It gives derivatives of any order if n > 0 and anti-derivatives of any order if n < 0.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.325
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2009
Admission routes1
Has abstractyes

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