1999
DOI: 10.1016/s0304-3975(99)00031-6
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A complete and efficiently computable topological classification of D-dimensional linear cellular automata over Zm

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Cited by 54 publications
(37 citation statements)
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“…LCA over n m have been strongly investigated in the case n = 1 and all the dynamical properties have been characterized in terms of the 1 × 1 matrices (i.e., coefficients) defining the local rule, in any dimension too [23,3].…”
Section: Definition 3 (Linear Cellular Automata) a Linear Cellular Amentioning
confidence: 99%
See 1 more Smart Citation
“…LCA over n m have been strongly investigated in the case n = 1 and all the dynamical properties have been characterized in terms of the 1 × 1 matrices (i.e., coefficients) defining the local rule, in any dimension too [23,3].…”
Section: Definition 3 (Linear Cellular Automata) a Linear Cellular Amentioning
confidence: 99%
“…[23]). Let ( m , F ) be a LCA where the local rule f : ( m ) 2r+1 → m is defined by 2r + 1 coeffiecients m −r , .…”
mentioning
confidence: 99%
“…In the following we restrict our attention to linear CA; that is, CA which are based on a linear local rule (they are sometimes called additive CA). Despite their apparent simplicity, linear CA may exhibit many complex behaviors (see for example [6,8,12,11,13,16]). Linear CA have been used for pattern generation, design of error correcting codes and cipher systems, generation of hashing functions, etc.…”
Section: Inverse4(f (X) M) → G(x)mentioning
confidence: 99%
“…In the following we restrict our attention to linear CA, that is, CA which are based on a linear local rule. Despite of their apparent simplicity, linear CA may exhibit many complex behaviors (see for example [6][7][8][9]). Linear CA have been used for pattern generation, design of error correcting codes and cipher systems, generation of hashing functions, etc.…”
Section: Definitions and Notationmentioning
confidence: 99%