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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.
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 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 ...
The characteristic equation, also known as the determinantal equation, [1] [2] [3] is the equation obtained by equating the characteristic polynomial to zero. In spectral graph theory , the characteristic polynomial of a graph is the characteristic polynomial of its adjacency matrix .
It is easy to detect the structure of a linear-feedback shift register with appropriate tests [41] such as the linear complexity test implemented in the TestU01 suite; a Boolean circulant matrix initialized from consecutive bits of an LFSR will never have rank greater than the degree of the polynomial.
In mathematics (including combinatorics, linear algebra, and dynamical systems), a linear recurrence with constant coefficients [1]: ch. 17 [2]: ch. 10 (also known as a linear recurrence relation or linear difference equation) sets equal to 0 a polynomial that is linear in the various iterates of a variable—that is, in the values of the elements of a sequence.
The closed-loop poles, or eigenvalues, are obtained by solving the characteristic equation + =. In general, the solution will be n complex numbers where n is the order of the characteristic polynomial. The preceding is valid for single-input-single-output systems (SISO).
The objective is to calculate the coefficients c k of the characteristic polynomial of the n×n matrix A, () = = ,where, evidently, c n = 1 and c 0 = (−1) n det A. The coefficients c n-i are determined by induction on i, using an auxiliary sequence of matrices