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Maximum-length sequence

Maximum-length sequence 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 Maximum-length sequence rather than just read about it. In short: A maximum-length sequence (MLS) is a type of pseudorandom binary sequence. They are bit sequences generated using maximal linear-feedback shift registers and are so called because they are periodic and reproduce every binary sequence (except the zero vector) that can be represented by the shift registers (i.e., for length-m registers they produce a sequence of length 2m − 1).

Maximum-length sequence — main illustration
Maximum-length sequence — illustration

Key takeaways

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

Reference excerpt

A maximum-length sequence (MLS) is a type of pseudorandom binary sequence. They are bit sequences generated using maximal linear-feedback shift registers and are so called because they are periodic and reproduce every binary sequence (except the zero vector) that can be represented by the shift registers (i.e., for length-m registers they produce a sequence of length 2m − 1). An MLS is also sometimes called an n-sequence or an m-sequence. MLSs are spectrally flat, with the exception of a near-zero DC term. These sequences may be represented as coefficients of primitive polynomials in a polynomial ring over Z/2Z. Practical applications for MLS include measuring impulse responses (e.g., of room reverberation or arrival times from towed sources in the ocean). They are also used as a basis for deriving pseudo-random sequences in digital communication systems that employ direct-sequence spread spectrum and frequency-hopping spread spectrum transmission systems, and in the efficient design of some fMRI experiments.

Generation

MLS are generated using maximal linear-feedback shift registers. An MLS-generating system with a shift register of length 4 is shown in Fig. 1. It can be expressed using the following recursive relation:

{ a 3 [ n + 1 ] = a 0 [ n ] + a 1 [ n ] a 2 [ n + 1 ] = a 3 [ n ] a 1 [ n + 1 ] = a 2 [ n ] a 0 [ n + 1 ] = a 1 [ n ] {\displaystyle {\begin{cases}a_{3}[n+1]=a_{0}[n]+a_{1}[n]\\a_{2}[n+1]=a_{3}[n]\\a_{1}[n+1]=a_{2}[n]\\a_{0}[n+1]=a_{1}[n]\end{cases}}}

where n is the time index and + {\displaystyle +} represents modulo-2 addition. For bit values 0 = FALSE or 1 = TRUE, this is equivalent to the XOR operation. As MLS are periodic and shift registers cycle through every possible binary value (with the exception of the zero vector), registers can be initialized to any state, with the exception of the zero vector.

Polynomial interpretation A polynomial over GF(2) can be associated with the linear-feedback shift register. It has degree of the length of the shift register, and has coefficients that are either 0 or 1, corresponding to the taps of the register that feed the xor gate. For example, the polynomial corresponding to Figure 1 is x 4 + x + 1 {\displaystyle x^{4}+x+1} . A necessary and sufficient condition for the sequence generated by a LFSR to be maximal length is that its corresponding polynomial be primitive.

Implementation MLS are inexpensive to implement in hardware or software, and relatively low-order feedback shift registers can generate long sequences; a sequence generated using a shift register of length 20 is 220 − 1 samples long (1,048,575 samples).

Properties of maximum-length sequences MLS have the following properties, as formulated by Solomon Golomb.

Balance property The occurrence of 0 and 1 in the sequence should be approximately the same. More precisely, in a maximum-length sequence of length 2 n − 1 {\displaystyle 2^{n}-1} there are 2 n − 1 {\displaystyle 2^{n-1}} ones and 2 n − 1 − 1 {\displaystyle 2^{n-1}-1} zeros. The number of ones equals the number of zeros plus one, since the state containing only zeros cannot occur.

Run property A "run" is a sub-sequence of consecutive "1"s or consecutive "0"s within the MLS concerned. The number of runs is the number of such sub-sequences. Of all the "runs" (consisting of "1"s or "0"s) in the sequence :

One half of the runs are of length 1. One quarter of the runs are of length 2. One eighth of the runs are of length 3. ... etc. ...

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Maximum-length sequence

Start with the simplest possible case. Write down what Maximum-length sequence 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 Maximum-length sequence 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 Maximum-length sequence 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 Maximum-length sequence

In research
Maximum-length sequence 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 Maximum-length sequence 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
Maximum-length sequence is common in secondary-school and first-year university syllabi. It links to neighbouring topics Binary sequences, Polynomials, Pseudorandomness, so understanding it makes those chapters shorter.
In everyday life
Look for Maximum-length sequence 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 Maximum-length sequence in 20 minutes

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

Frequently asked questions

What is Maximum-length sequence in simple terms?

A maximum-length sequence (MLS) is a type of pseudorandom binary sequence. They are bit sequences generated using maximal linear-feedback shift registers and are so called because they are periodic and reproduce every binary sequence (except the zero vector) that can be represented by the shift reg…

Why does Maximum-length sequence 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 Maximum-length sequence?

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 Maximum-length sequence.

Tags

  • Binary sequences
  • Polynomials
  • Pseudorandomness

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