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Piecewise-Defined Functions01:28

Piecewise-Defined Functions

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Piecewise defined functions are mathematical models where different expressions define a function over distinct intervals of the domain. These functions are useful for representing systems with varying behaviors depending on input values.For example, the function:  uses a linear rule for inputs less than or equal to –1 and a quadratic rule for values greater than –1. Although it has two formulas, it still defines a single function.Another common type is the absolute value...
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Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

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In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
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Decreasing Function01:20

Decreasing Function

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A decreasing function describes a relationship where the output consistently declines as the input increases. This means that for any two input values, if one is greater than the other, the corresponding output is smaller. Mathematically, a function f is decreasing on an interval I if for every x1 < x2​ in I, f (x1) > f (x2). This type of behavior is visually identified on a graph that slopes downward from left to right.The nature of a function can be analyzed by calculating...
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Introduction to Polynomial Functions01:26

Introduction to Polynomial Functions

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Polynomial functions are fundamental elements in algebra and calculus, defined by expressions that combine variables and constants through addition, subtraction, and multiplication, with the variable raised to nonnegative integer exponents. A general polynomial function of degree n is given byWhere an ≠ 0. The term anxn is the leading term, and an is the leading coefficient, while a0 is referred to as the constant term.Characteristics and ClassificationPolynomials are categorized by their...
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Fundamental Theorem of Algebra01:30

Fundamental Theorem of Algebra

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The Fundamental Theorem of Algebra is central to the study of polynomial equations, asserting that every non-constant polynomial with complex coefficients has at least one complex zero. This means that a polynomial of degree n ≥ 1, written as:  with an ≠ 0, has at least one solution in the complex number system. Since the set of real numbers is a subset of complex numbers, this theorem applies equally to polynomials with real coefficients.Building on this result, the...
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Limits at Infinity01:24

Limits at Infinity

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The function that decreases as the input becomes very large provides a clear example of how mathematical functions can behave at extreme values. When the input increases continuously, the output becomes smaller and smaller, getting closer to a particular fixed value. Although the output never actually reaches this value, it moves nearer to it without limit. This behavior is a fundamental concept in understanding how functions behave as the input grows indefinitely. The graphical representation...
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Related Experiment Video

Updated: Dec 2, 2025

Inducible and Reversible Dominant-negative DN Protein Inhibition
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A Probabilistic Characterization of Negative Definite Functions.

Fuchang Gao1

  • 1Department of Mathematics, University of Idaho, Moscow, ID, USA.

High Dimensional Probability
|November 4, 2020
PubMed
Summary
This summary is machine-generated.

Continuous functions are negative definite if they are polynomially bounded and meet a specific probabilistic inequality. This finding simplifies the characterization of negative definite functions in mathematical analysis.

Keywords:
42A8260E10Fourier inversion theoremLévy–Khintchine representationNegative definite functionPolynomially boundedPrimary: 60E15Secondary: 42B10

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Area of Science:

  • Mathematical Analysis
  • Probability Theory
  • Functional Analysis

Background:

  • Negative definite functions are crucial in various fields, including probability and statistics.
  • Characterizing these functions is essential for theoretical advancements.
  • Previous work by Lifshits et al. established part of the condition.

Purpose of the Study:

  • To provide a complete and simplified characterization of continuous negative definite functions on ℝ^d.
  • To establish the equivalence between polynomial boundedness, a specific probabilistic inequality, and the property of being negative definite.
  • To offer a new proof for the 'if' part of the theorem.

Main Methods:

  • Utilizing Fourier transforms of tempered distributions.
  • Applying concepts from stochastic processes and random vector analysis.
  • Leveraging advanced mathematical analysis techniques.

Main Results:

  • A continuous function f on ℝ^d is negative definite if and only if it is polynomially bounded.
  • The function must also satisfy the inequality E[(f(X) - f(Y))²] ≤ C E[|X - Y|²] for all i.i.d. random vectors X and Y.
  • The proof establishes a novel connection between analytical properties and probabilistic inequalities.

Conclusions:

  • The study provides a comprehensive and elegant characterization of negative definite functions.
  • The findings simplify the identification and application of negative definite functions in theoretical research.
  • The proof methodology offers new insights into the interplay between function theory and probability.