# Difference between revisions of "Linear Time Invarient System"

(→LTI system properties) |
|||

Line 6: | Line 6: | ||

A system is considered to be a Linear Time Invariant when it satisfies the two basic criteria implied in its name, one it must be linear and two it must be time invariant. A Linear system is characterized by two properties superposition (additivity) and scaling (homogeneity). The superposition principal says that for any linear system a linear combination of solutions to the system is also a solution to the same linear system. The principal of scaling implies that if you adjust your scale an input by N amount, your output will also be adjusted by N amount. An example of a linear system then would be, |
A system is considered to be a Linear Time Invariant when it satisfies the two basic criteria implied in its name, one it must be linear and two it must be time invariant. A Linear system is characterized by two properties superposition (additivity) and scaling (homogeneity). The superposition principal says that for any linear system a linear combination of solutions to the system is also a solution to the same linear system. The principal of scaling implies that if you adjust your scale an input by N amount, your output will also be adjusted by N amount. An example of a linear system then would be, |
||

− | ::<math>x_1(t)</math> |
+ | ::<math>x_1(t)\!</math> |

− | ::<math>x_2(t)</math> |
+ | ::<math>x_2(t)\!</math> |

− | ::<math>y_1(t) = H(x_1(t))</math> |
+ | ::<math>y_1(t) = H(x_1(t))\!</math> |

− | ::<math>y_2(t) = H(x_2(t))</math> |
+ | ::<math>y_2(t) = H(x_2(t))\!</math> |

− | ::<math>Ay_1(t) + By_2(t) = H(Ax_2(t) + Bx_1(t))</math> |
+ | ::<math>Ay_1(t) + By_2(t) = H(Ax_2(t) + Bx_1(t))\!</math> |

for any scalar values of A and B. |
for any scalar values of A and B. |
||

Time invariance of a system means that for any input <math>x(t)</math> by some amount of time T the out put will also be adjusted by that amount of time. This implies that for, |
Time invariance of a system means that for any input <math>x(t)</math> by some amount of time T the out put will also be adjusted by that amount of time. This implies that for, |
||

− | ::<math>x(t - T)</math> |
+ | ::<math>x(t - T)\!</math> |

− | ::<math>y(t - T) = H(x(t - T))</math> |
+ | ::<math>y(t - T) = H(x(t - T))\!</math> |

<br> |
<br> |

## Revision as of 22:31, 12 October 2006

## LTI systems

LTI System theory is a powerful and widely used concept in electrical engineering. It has applictions in circuit anlysis, control theory , and our main topic of interest signal processing.

### LTI system properties

A system is considered to be a Linear Time Invariant when it satisfies the two basic criteria implied in its name, one it must be linear and two it must be time invariant. A Linear system is characterized by two properties superposition (additivity) and scaling (homogeneity). The superposition principal says that for any linear system a linear combination of solutions to the system is also a solution to the same linear system. The principal of scaling implies that if you adjust your scale an input by N amount, your output will also be adjusted by N amount. An example of a linear system then would be,

for any scalar values of A and B.

Time invariance of a system means that for any input by some amount of time T the out put will also be adjusted by that amount of time. This implies that for,

Related Links