(System Characterized By Linear Constant-Coefficient Differential Equations)
(System Characterized By Linear Constant-Coefficient Differential Equations)
 
(29 intermediate revisions by the same user not shown)
Line 2: Line 2:
 
<math> \sum_{k=0}^{N}a_k\frac {d^ky(t)}{dt^k} = \sum_{k=0}^{M}b_k\frac {d^kx(t)}{dt^k} </math>
 
<math> \sum_{k=0}^{N}a_k\frac {d^ky(t)}{dt^k} = \sum_{k=0}^{M}b_k\frac {d^kx(t)}{dt^k} </math>
  
=<math>Y(jw)=H(jw)X(jw),  H(jw)=\frac{Y(jw)}{X(jw)}</math>
+
<math>Y(jw)=H(jw)X(jw),  H(jw)=\frac{Y(jw)}{X(jw)}</math>
 +
 
 +
to obtain equation above from the top equation
 +
 
 +
<math>\mathcal{F}(\sum_{k=0}^{N}a_k\frac {d^ky(t)}{dt^k}) =\mathcal{F}(\sum_{k=0}^{M}b_k\frac {d^kx(t)}{dt^k})</math>
 +
 
 +
<math>\sum_{k=0}^{N}a_k\mathcal{F}(\frac {d^ky(t)}{dt^k}) = \sum_{k=0}^{M}b_k\mathcal{F}(\frac {d^kx(t)}{dt^k})</math>
 +
 
 +
<math>\sum_{k=0}^{N}a_k(jw)^kY(jw)=\sum_{k=0}^{M}b_k(jw)^kX(jw)</math>
 +
 
 +
<math>Y(jw)[\sum_{k=0}^{N}a_k(jw)^k]=X(jw)[\sum_{k=0}^{M}b_k(jw)^k]</math>
 +
 
 +
<math>Y(jw)=\frac{Y(jw)}{X(jw)}=\frac{\sum_{k=0}^{M}b_k(jw)^k}{\sum_{k=0}^{N}a_k(jw)^k}</math>
 +
 
 
== Example ==
 
== Example ==
 +
Consider a LTI system that is chracterized by the differential equation
 +
 +
 +
<math> \frac{d^2y(t)}{dt^2}+4\frac{dy(t)}{dt}+3y(t) = \frac{dx(t)}{dt}+2x(t)</math>
 +
 +
 +
 +
<math> H(jw)=\frac{(jw)+2}{(jw)^2+4(jw)+3}</math>
 +
 +
 +
<math>H(jw)=\frac{jw+2}{(jw+1)(jw+3)}</math>
 +
 +
<math>H(jw)=\frac{\frac{1}{2}}{jw+1} + \frac{\frac{1}{2}}{jw+3}</math>
 +
 +
<math>h(t)=\frac{1}{2}e^{-t}u(t)+\frac{1}{2}e^{-3t}u(t)</math>
 +
 +
 +
Consider the system above, and suppose that the input is
 +
 +
<math>x(t)=e^{-t}u(t)</math>
 +
 +
<math> Y(jw)=H(jw)X(jw)=[\frac{jw+2}{(jw+1)(jw+3)}][\frac{1}{jw+1}]</math>
 +
 +
<math>=\frac{jw+2}{(jw+1)^2(jw+3)}</math>
 +
 +
<math>Y(jw)=\frac{A_{11}}{jw+1}+\frac{A_{12}}{(jw+1)^2}+\frac{A_{21}}{jw+3}</math>
 +
 +
<math>A_{11}=\frac{1}{4}, A_{12}=\frac{1}{2},A_{21}=-\frac{1}{4}</math>
 +
 +
<math>Y(jw)=\frac{\frac{1}{4}}{jw+1}+\frac{\frac{1}{2}}{(jw+1)^2}-\frac{\frac{1}{4}}{jw+4}</math>
 +
 +
<math>y(t)=[\frac{1}{4}e^{-t}+\frac{1}{2}te^{-t}-\frac{1}{4}e^{-3t}]u(t)</math>

Latest revision as of 17:08, 24 October 2008

System Characterized By Linear Constant-Coefficient Differential Equations

$ \sum_{k=0}^{N}a_k\frac {d^ky(t)}{dt^k} = \sum_{k=0}^{M}b_k\frac {d^kx(t)}{dt^k} $

$ Y(jw)=H(jw)X(jw), H(jw)=\frac{Y(jw)}{X(jw)} $

to obtain equation above from the top equation

$ \mathcal{F}(\sum_{k=0}^{N}a_k\frac {d^ky(t)}{dt^k}) =\mathcal{F}(\sum_{k=0}^{M}b_k\frac {d^kx(t)}{dt^k}) $

$ \sum_{k=0}^{N}a_k\mathcal{F}(\frac {d^ky(t)}{dt^k}) = \sum_{k=0}^{M}b_k\mathcal{F}(\frac {d^kx(t)}{dt^k}) $

$ \sum_{k=0}^{N}a_k(jw)^kY(jw)=\sum_{k=0}^{M}b_k(jw)^kX(jw) $

$ Y(jw)[\sum_{k=0}^{N}a_k(jw)^k]=X(jw)[\sum_{k=0}^{M}b_k(jw)^k] $

$ Y(jw)=\frac{Y(jw)}{X(jw)}=\frac{\sum_{k=0}^{M}b_k(jw)^k}{\sum_{k=0}^{N}a_k(jw)^k} $

Example

Consider a LTI system that is chracterized by the differential equation


$ \frac{d^2y(t)}{dt^2}+4\frac{dy(t)}{dt}+3y(t) = \frac{dx(t)}{dt}+2x(t) $


$ H(jw)=\frac{(jw)+2}{(jw)^2+4(jw)+3} $


$ H(jw)=\frac{jw+2}{(jw+1)(jw+3)} $

$ H(jw)=\frac{\frac{1}{2}}{jw+1} + \frac{\frac{1}{2}}{jw+3} $

$ h(t)=\frac{1}{2}e^{-t}u(t)+\frac{1}{2}e^{-3t}u(t) $


Consider the system above, and suppose that the input is

$ x(t)=e^{-t}u(t) $

$ Y(jw)=H(jw)X(jw)=[\frac{jw+2}{(jw+1)(jw+3)}][\frac{1}{jw+1}] $

$ =\frac{jw+2}{(jw+1)^2(jw+3)} $

$ Y(jw)=\frac{A_{11}}{jw+1}+\frac{A_{12}}{(jw+1)^2}+\frac{A_{21}}{jw+3} $

$ A_{11}=\frac{1}{4}, A_{12}=\frac{1}{2},A_{21}=-\frac{1}{4} $

$ Y(jw)=\frac{\frac{1}{4}}{jw+1}+\frac{\frac{1}{2}}{(jw+1)^2}-\frac{\frac{1}{4}}{jw+4} $

$ y(t)=[\frac{1}{4}e^{-t}+\frac{1}{2}te^{-t}-\frac{1}{4}e^{-3t}]u(t) $

Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva