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In computing, a linear-feedback shift register (LFSR) is a shift register whose input bit is a linear function of its previous state. The most commonly used linear function of single bits is exclusive-or (XOR). Thus, an LFSR is most often a shift register whose input bit is driven by the XOR of some bits of the overall shift register value.
Others have mentioned this, but to summarize: the Galois and Fibonacci LFSR should have the numbering of their taps reversed. Specifications like USB define Galois polynomials e.g. x^16 + x^5 + x^4 + x^3 + 1 which corresponds to taps at 16, 5, 4, 3. However, for industry, this is defined for a Galois LFSR with numbering starting from the left.
In their paper, [1] Meier and Steffelbach prove that a LFSR-based self-shrinking generator with a connection polynomial of length L results in an output sequence period of at least 2 L/2, and a linear complexity of at least 2 L/2-1. Furthermore, they show that any self-shrinking generator can be represented as a shrinking-generator.
The Berlekamp–Massey algorithm is an algorithm that will find the shortest linear-feedback shift register (LFSR) for a given binary output sequence. The algorithm will also find the minimal polynomial of a linearly recurrent sequence in an arbitrary field .
In cryptography, the shrinking generator is a form of pseudorandom number generator intended to be used in a stream cipher.It was published in Crypto 1993 by Don Coppersmith, Hugo Krawczyk and Yishay Mansour.
A is the output of the first LFSR whose generator polynomial is x → x 10 + x 3 + 1, and initial state is 1111111111 2. B is the output of the second LFSR whose generator polynomial is x → x 10 + x 9 + x 8 + x 6 + x 3 + x 2 + 1 and initial state is also 1111111111 2.
In fact, every linear-feedback shift register with maximum cycle length (which is 2 n − 1, where n is the length of the linear-feedback shift register) may be built from a primitive polynomial. [2] In general, for a primitive polynomial of degree m over GF(2), this process will generate 2 m − 1 pseudo-random bits before repeating the same ...
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 2 m − 1).