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Lee distance

Lee distance is a science 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 Lee distance rather than just read about it. In short: In coding theory, the Lee distance is a distance between two strings x 1 x 2 … x n {\displaystyle x_{1}x_{2}\dots x_{n}} and y 1 y 2 … y n {\displaystyle y_{1}y_{2}\dots y_{n}} of equal length n over the q-ary alphabet {0, 1, …, q − 1} of size q ≥ 2. It is a metric defined as ∑ i = 1 n min ( | x i − y i | , q − | x i − y i | ) . {\displaystyle \sum _{i=1}^{n}\min(|x_{i}-y_{i}|,\,q-|x_{i}-y_{i}|).} If q = 2 or q = 3…

Key takeaways

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

Reference excerpt

In coding theory, the Lee distance is a distance between two strings x 1 x 2 … x n {\displaystyle x_{1}x_{2}\dots x_{n}} and y 1 y 2 … y n {\displaystyle y_{1}y_{2}\dots y_{n}} of equal length n over the q-ary alphabet {0, 1, …, q − 1} of size q ≥ 2. It is a metric defined as

∑ i = 1 n min ( | x i − y i | , q − | x i − y i | ) . {\displaystyle \sum _{i=1}^{n}\min(|x_{i}-y_{i}|,\,q-|x_{i}-y_{i}|).}

If q = 2 or q = 3 the Lee distance coincides with the Hamming distance, because both distances are 0 for two single equal symbols and 1 for two single non-equal symbols. For q > 3 this is not the case anymore; the Lee distance between single letters can become bigger than 1. However, there exists a Gray isometry (weight-preserving bijection) between Z 4 {\displaystyle \mathbb {Z} _{4}} with the Lee weight and Z 2 2 {\displaystyle \mathbb {Z} _{2}^{2}} with the Hamming weight. Considering the alphabet as the additive group Zq, the Lee distance between two single letters x {\displaystyle x} and y {\displaystyle y} is the length of shortest path in the Cayley graph (which is circular since the group is cyclic) between them. More generally, the Lee distance between two strings of length n is the length of the shortest path between them in the Cayley graph of Z q n {\displaystyle \mathbf {Z} _{q}^{n}} . This can also be thought of as the quotient metric resulting from reducing Zn with the Manhattan distance modulo the lattice qZn. The analogous quotient metric on a quotient of Zn modulo an arbitrary lattice is known as a Mannheim metric or Mannheim distance. The metric space induced by the Lee distance is a discrete analog of the elliptic space.

Example If q = 6, then the Lee distance between 3140 and 2543 is 1 + 2 + 0 + 3 = 6.

History and application The Lee distance is named after William Chi Yuan Lee (李始元). It is applied for phase modulation while the Hamming distance is used in case of orthogonal modulation. The Berlekamp code is an example of code in the Lee metric. Other significant examples are the Preparata code and Kerdock code; these codes are non-linear when considered over a field, but are linear over a ring.

References

Lee, C. Y. (1958), "Some properties of nonbinary error-correcting codes", IRE Transactions on Information Theory, 4 (2): 77–82, doi:10.1109/TIT.1958.1057446 Berlekamp, Elwyn R. (1968), Algebraic Coding Theory, McGraw-Hill Voloch, Jose Felipe; Walker, Judy L. (1998). "Lee Weights of Codes from Elliptic Curves". In Vardy, Alexander (ed.). Codes, Curves, and Signals: Common Threads in Communications. Springer Science & Business Media. ISBN 978-1-4615-5121-8.

Worked examples

Example 1 — a first encounter with Lee distance

Start with the simplest possible case. Write down what Lee distance claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, 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 Lee distance 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 Lee distance 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 Lee distance

In research
Lee distance appears in science 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 Lee distance 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
Lee distance is common in secondary-school and first-year university syllabi. It links to neighbouring topics Coding theory, String metrics, so understanding it makes those chapters shorter.
In everyday life
Look for Lee distance 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 Lee distance in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Lee distance 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 Lee distance out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Lee distance in simple terms?

In coding theory, the Lee distance is a distance between two strings x 1 x 2 … x n {\displaystyle x_{1}x_{2}\dots x_{n}} and y 1 y 2 … y n {\displaystyle y_{1}y_{2}\dots y_{n}} of equal length n over the q-ary alphabet {0, 1, …, q − 1} of size q ≥ 2. It is a metric defined as ∑ i = 1 n min ( | x i…

Why does Lee distance matter?

Because it connects several science 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 Lee distance?

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 Lee distance.

Tags

  • Coding theory
  • String metrics

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