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Signed measure

Signed measure is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Signed measure rather than just read about it. In short: In mathematics, a signed measure is a generalization of the concept of (positive) measure by allowing the set function to take negative values, i.e., to acquire sign. Definition There are two slightly different concepts of a signed measure, depending on whether or not one allows it to take infinite values.

Key takeaways

  • Signed measure belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Signed measure to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Signed measure from memory before moving on to harder problems.

Reference excerpt

In mathematics, a signed measure is a generalization of the concept of (positive) measure by allowing the set function to take negative values, i.e., to acquire sign.

Definition There are two slightly different concepts of a signed measure, depending on whether or not one allows it to take infinite values. Signed measures are usually only allowed to take finite real values, while some textbooks allow them to take infinite values. To avoid confusion, this article will call these two cases "finite signed measures" and "extended signed measures". Given a measurable space ( X , Σ ) {\displaystyle (X,\Sigma )} (that is, a set X {\displaystyle X} with a σ-algebra Σ {\displaystyle \Sigma } on it), an extended signed measure is a set function

μ : Σ → R ∪ { ∞ , − ∞ } {\displaystyle \mu :\Sigma \to \mathbb {R} \cup \{\infty ,-\infty \}}

such that μ ( ∅ ) = 0 {\displaystyle \mu (\varnothing )=0} and μ {\displaystyle \mu } is σ-additive – that is, it satisfies the equality

μ ( ⋃ n = 1 ∞ A n ) = ∑ n = 1 ∞ μ ( A n ) {\displaystyle \mu \left(\bigcup _{n=1}^{\infty }A_{n}\right)=\sum _{n=1}^{\infty }\mu (A_{n})}

for any sequence A 1 , A 2 , … , A n , … {\displaystyle A_{1},A_{2},\ldots ,A_{n},\ldots } of disjoint sets in Σ . {\displaystyle \Sigma .}

The series on the right must converge absolutely when the value of the left-hand side is finite. One consequence is that an extended signed measure can take + ∞ {\displaystyle +\infty } or − ∞ {\displaystyle -\infty } as a value, but not both. The expression ∞ − ∞ {\displaystyle \infty -\infty } is undefined and must be avoided. A finite signed measure (a.k.a. real measure) is defined in the same way, except that it is only allowed to take real values. That is, it cannot take + ∞ {\displaystyle +\infty } or − ∞ . {\displaystyle -\infty .}

Finite signed measures form a real vector space, while extended signed measures do not because they are not closed under addition. On the other hand, measures are extended signed measures, but are not in general finite signed measures.

Examples Consider a non-negative measure ν {\displaystyle \nu } on the space (X, Σ) and a measurable function f: X → R such that

∫ X | f ( x ) | d ν ( x ) < ∞ . {\displaystyle \int _{X}\!|f(x)|\,d\nu (x)<\infty .}

Then, a finite signed measure is given by

μ ( A ) = ∫ A f ( x ) d ν ( x ) {\displaystyle \mu (A)=\int _{A}\!f(x)\,d\nu (x)}

for all A in Σ. This signed measure takes only finite values. To allow it to take +∞ as a value, one needs to replace the assumption about f being absolutely integrable with the more relaxed condition

∫ X f − ( x ) d ν ( x ) < ∞ , {\displaystyle \int _{X}\!f^{-}(x)\,d\nu (x)<\infty ,}

where f−(x) = max(−f(x), 0) is the negative part of f.

Properties What follows are two results which will imply that an extended signed measure is the difference of two non-negative measures, and a finite signed measure is the difference of two finite non-negative measures. The Hahn decomposition theorem states that given a signed measure μ, there exist two measurable sets P and N such that:

P∪N = X and P∩N = ∅; μ(E) ≥ 0 for each E in Σ such that E ⊆ P — in other words, P is a positive set; μ(E) ≤ 0 for each E in Σ such that E ⊆ N — that is, N is a negative set. Moreover, this decomposition is unique up to adding to/subtracting μ-null sets from P and N. Consider then two non-negative measures μ+ and μ− defined by

μ + ( E ) = μ ( P ∩ E ) {\displaystyle \mu ^{+}(E)=\mu (P\cap E)}

and

μ − ( E ) = − μ ( N ∩ E ) {\displaystyle \mu ^{-}(E)=-\mu (N\cap E)}

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Signed measure

Start with the simplest possible case. Write down what Signed measure claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Signed measure before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Signed measure ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Signed measure

In research
Signed measure appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Signed measure in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Signed measure is common in secondary-school and first-year university syllabi. It links to neighbouring topics Integral calculus, Measures (measure theory), Sign (mathematics), so understanding it makes those chapters shorter.
In everyday life
Look for Signed measure outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Signed measure in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Signed measure means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Signed measure out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Signed measure in simple terms?

In mathematics, a signed measure is a generalization of the concept of (positive) measure by allowing the set function to take negative values, i.e., to acquire sign. Definition There are two slightly different concepts of a signed measure, depending on whether or not one allows it to take infinite…

Why does Signed measure matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Signed measure?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Signed measure.

Tags

  • Integral calculus
  • Measures (measure theory)
  • Sign (mathematics)

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