Seven data normalization methods | The nine prototypical ILD functions (min: 0.0 and max: 100, with ±6 %) | ||||||||
---|---|---|---|---|---|---|---|---|---|

(A) | (B) | (C) | (D) | (E) | (F) | (G) | (H) | (I) | |

(1) Vn (i, j) = X_{
n
}(i, j) − μ_{
n
}
| -46/49 | -67/68 | -69/48 | -37/59 | -23/73 | -43/71 | -64/60 | -42/46 | -5.7/8 |

(2) Vn (i, j) = X_{
n
}(i, j)/max{max{X_{
n
}(i, j)}}
| 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 |

(3) Vn (i, j) = X_{
n
}(i, j)/max{X_{
n
}(i, j)}
| 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.01/1 | 0.02/1 | 0.24/1 |

(4) Vn (i, j) = X_{
n
}(i, j)/σ_{
n
}
| 0.04/2 | 0.02/2 | 0.04/2 | 0.06/2 | 0.04/3 | 0.03/3 | 0.02/2 | 0.1/23 | 0.6/51 |

(5) Vn (i, j) = log_{2}(X_{n}(i, j)) − log_{2}(μ_{n})
| -4.6/1 | -6/1.7 | -5.3/1 | -4/1.3 | -4.3/2 | -4.6/2 | -4.8/1 | -4.4/1 | -1/0.7 |

(6) Vn (i, j) = $\frac{{\mathrm{X}}_{\mathrm{n}}\left(\mathrm{i},\mathrm{j}\right)}{{{\displaystyle \sum}}_{\mathrm{n}}{\mathrm{X}}_{\mathrm{n}}}\xb7{\mathrm{\mu}}_{\mathrm{n}}$
| 0.1/7 | 0.1/7 | 0.08/7 | 0.09/7 | 0.08/7 | 0.09/7 | 0.09/7 | 0.23/7 | 0.1/7. |

(7) Vn (i, j) = $\frac{{\mathrm{X}}_{\mathrm{n}}\left(\mathrm{i},\mathrm{j}\right)-{\mathrm{\mu}}_{\mathrm{n}}}{{\mathrm{\sigma}}_{\mathrm{n}}}$
| -1.1/1 | -1.1/1 | -1.8/1 | -1/1.7 | -0.7/2 | -1.3/2 | -1.5/1 | -1.8/1 | -1.4/1 |