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Hadamard -Sylvester Matrix Self-Similarity by substitution and reparatitioning


A long time back I ran across this in an electrical engineering magazine.
With the right starting matric Haramard -Silvester Matrix 
self-Similaroty gives a Pascal's triangle like result.
I just this morning figured out how to repartition the matrices to give 
usable arrasys!
(* Fibonacci Matrix for Matrix Markov: 2by2*)
t[n_, m_] := If[ n == m == 1, 0, 1]
(* substitution step*)
a = Table[t[n, m]*t[i, j], {n, 1, 2}, {m, 1, 2}, {i, 1, 2}, {j, 1, 2}];
(* first level Hadamard -Sylvester Matrix self-Similarity repartitution: 
4by4*)
M = Flatten[Table[{Flatten[Table[a[[
      n, m]][[1, i]], {n,
           1, 2}, {i, 1, 2}]], Flatten[Table[a[[n, m]][[2,
            i]], {n, 1, 2}, {i, 1, 2}]]}, {m, 1, 2}], 1]
aa = Table[M[[n, m]]*M[[i, j]], {n, 1, 4}, {m, 1, 4}, {i, 1, 4}, {j, 1, 4}];
(* second level Hadamard -Sylvester Matrix self-Similarity 
repartitution: 16 by16*)
M2 = Flatten[Table[{Flatten[Table[aa[[
      n, m]][[1, i]], {n,
           1, 4}, {i, 1, 4}]], Flatten[Table[aa[[n, m]][[2,
            i]], {n, 1, 4}, {i, 1, 4}]], Flatten[Table[aa[[
      n, m]][[3, i]], {n,
           1, 4}, {i, 1, 4}]], Flatten[Table[aa[[
      n, m]][[4, i]], {n,
           1, 4}, {i, 1, 4}]]}, {m, 1, 4}], 1]

{{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1},
 {0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 1, 1},
 {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1},
{0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 1, 1, 1, 1},
{ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1},
{0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 1, 1, 0, 0, 1, 1},
 {0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1},
{0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1},
{ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1},
 {0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1},
{0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1},
{0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1},
{0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1},
{0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1},
 { 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1}.
{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}}


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