Abstract:Ahstrurt-An implementation of Elias coding for input-restricted channels is presented and analyzed. This is a variabk-to-fixed length coding method that uses finite-precision arithmetic and can work at rates arbitrarily close to channel capacity as the precision is increased. The method offers a favorable tradeoff between complexity and coding efficiency. For example, in experiments with the 12, 7 1 runlength constrained channel, a coding efficiency of 0.9977 is observed, which is significantly better than wha… Show more
“…The reader can verify that the sets E 0 , E (1) 1 , E (2) 1 , E (1) 2 , and E (2) 2 have total weights 15, 15, 7, 16, and 16, respectively, as desired (in fact, the weights of E (1) 2 and E (2) 2 are forced to be 16).…”
Section: Consistent Splittingmentioning
confidence: 99%
“…Recall that the capacity, cap(S), of a constraint S is de ned by cap(S) = lim !1 (1=`) log jS`j ; (2) where the limit is known to exist 12, Section 3.2.1] (hereafter all logarithms are taken to base 2). Since jS qm j jS q j m for any choice of positive integers q and m, it follows that cap(S) = lim m!1 (1=(qm)) log jS qm j (1=q) log jS q j ; that is, the limit in the right-hand side of (2) is taken over elements each of which is an upper bound on cap(S).…”
Section: Block Codesmentioning
confidence: 99%
“…A state splitting of a graph G (called an out-splitting in 12, Section 4.1] and sometimes called a round of state splitting) is obtained by partitioning the set, E u , of outgoing edges from each state u of G into N = N(u) disjoint sets, E u = E (1) u E (2) u E (N) u ;…”
Section: State Splittingmentioning
confidence: 99%
“…(5) replacing u by descendant states u (1) ; u (2) ; : : : ; u (N) , assigning E (r) u as outgoing edges from u (r) , and replicating all edges incoming to a state v to each of its descendants v (r) .…”
Section: State Splittingmentioning
confidence: 99%
“…The resulting split graph H will have ve states, 0, 1 (1) , 1 (2) , 2 (1) , and 2 (2) , and the induced (A H ; n)-super-vector is The following modi cation of Proposition 4.4 of 12] shows that in general there always is an x-consistent splitting whenever we need one. Proposition 4 Let G be an irreducible graph which does not have out-degree at most n and let x be an (A G ; n)-super-vector.…”
A method is presented for designing lossless sliding-block compression schemes that map constrained sequences onto unconstrained ones. The new compression scheme is incorporated into a coding technique for noisy constrained channels, which has applications to magnetic and optical storage. As suggested recently by Immink, the use of a lossless compression code can improve the performance of a modi ed concatenation scheme where the positions of the error-correcting code and constrained code are reversed (primarily in order to eliminate error-propagation due to the constrained code). Examples are presented that demonstrate the advantage of using sliding-block compression over block compression in a noisy constrained setting.
“…The reader can verify that the sets E 0 , E (1) 1 , E (2) 1 , E (1) 2 , and E (2) 2 have total weights 15, 15, 7, 16, and 16, respectively, as desired (in fact, the weights of E (1) 2 and E (2) 2 are forced to be 16).…”
Section: Consistent Splittingmentioning
confidence: 99%
“…Recall that the capacity, cap(S), of a constraint S is de ned by cap(S) = lim !1 (1=`) log jS`j ; (2) where the limit is known to exist 12, Section 3.2.1] (hereafter all logarithms are taken to base 2). Since jS qm j jS q j m for any choice of positive integers q and m, it follows that cap(S) = lim m!1 (1=(qm)) log jS qm j (1=q) log jS q j ; that is, the limit in the right-hand side of (2) is taken over elements each of which is an upper bound on cap(S).…”
Section: Block Codesmentioning
confidence: 99%
“…A state splitting of a graph G (called an out-splitting in 12, Section 4.1] and sometimes called a round of state splitting) is obtained by partitioning the set, E u , of outgoing edges from each state u of G into N = N(u) disjoint sets, E u = E (1) u E (2) u E (N) u ;…”
Section: State Splittingmentioning
confidence: 99%
“…(5) replacing u by descendant states u (1) ; u (2) ; : : : ; u (N) , assigning E (r) u as outgoing edges from u (r) , and replicating all edges incoming to a state v to each of its descendants v (r) .…”
Section: State Splittingmentioning
confidence: 99%
“…The resulting split graph H will have ve states, 0, 1 (1) , 1 (2) , 2 (1) , and 2 (2) , and the induced (A H ; n)-super-vector is The following modi cation of Proposition 4.4 of 12] shows that in general there always is an x-consistent splitting whenever we need one. Proposition 4 Let G be an irreducible graph which does not have out-degree at most n and let x be an (A G ; n)-super-vector.…”
A method is presented for designing lossless sliding-block compression schemes that map constrained sequences onto unconstrained ones. The new compression scheme is incorporated into a coding technique for noisy constrained channels, which has applications to magnetic and optical storage. As suggested recently by Immink, the use of a lossless compression code can improve the performance of a modi ed concatenation scheme where the positions of the error-correcting code and constrained code are reversed (primarily in order to eliminate error-propagation due to the constrained code). Examples are presented that demonstrate the advantage of using sliding-block compression over block compression in a noisy constrained setting.
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