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Algebraic Methods for Signal Processing and Communications by Richard E. Blahut, C.S. Burrus

By Richard E. Blahut, C.S. Burrus

Algorithms for computation are a important a part of either electronic sign seasoned­ cessing and decoders for error-control codes and the vital algorithms of the 2 topics percentage many similarities. each one topic makes wide use of the discrete Fourier remodel, of convolutions, and of algorithms for the inversion of Toeplitz structures of equations. electronic sign processing is now a longtime topic in its personal correct; it not has to be seen as a digitized model of analog sign strategy­ ing. Algebraic constructions have gotten extra vital to its improvement. a number of the ideas of electronic sign processing are legitimate in any algebraic box, even supposing usually at the least a part of the matter will certainly lie both within the actual box or the complicated box simply because that's the place the information originate. In different situations the alternative of box for computations could be as much as the set of rules dressmaker, who frequently chooses the genuine box or the complicated box due to familiarity with it or since it is acceptable for the actual program. nonetheless, it really is applicable to catalog the numerous algebraic fields in a manner that's obtainable to scholars of electronic sign processing, in hopes of stimulating new purposes to engineering tasks.

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The set Z[w], known as a set of algebraic integers, is no longer a field, but it is a commutative ring with identity. The sum of two elements of Z[w] is an element of Z[w] and, because wm is an integer combination of smaller powers of w, the product of two elements of Z[w] is an element of Z[w]. In particular, if m is a power of 2, multiplication is simple because wm = -1. The ring Z [ei27r / 4], consisting of the set {a + j b} where a and b are integers, is known as the ring of Gaussian integers.

A ring R is a set that has two arithmetic operations defined on it: addition and multiplication, such that the following properties are satisfied. 1) (Addition Axiom) The set R is closed under addition, and addition is associative and commutative a (a+ b) + c, b+a. + (b + c) a+b There is an element called zero and denoted 0 such that a + 0 = a, and every element a has an element called the negative of a and denoted (-a) such that a + (-a) = O. Subtraction a - b is defined as a + (-b). 2) (Multiplication Axiom) The set R is closed under multiplication, and multiplication is associative a(bc) = (ab)e.

0 If GCD(b, n) i= 1, then the cyclic decimation v~ = V«bi» has period smaller than n - the period is n' = nIGCD(b, n). The following theorem relates the n'-point Fourier transform of the decimated vector v' to the n-point Fourier transform of the original vector v by first folding the spectrum V then cyclically decimating the folded spectrum. 3 Let GCD(b,n) cyclic decimation , Vi = V«bi» = n", n' = nln", and b' i = 0, ... , n' - 1 ' has Fourier transform , V k, - = V B'k'(mod where -Vk' and B' satisfies -1 = n" L n'), k' = 0, ...

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