which allows to relate initial values with eigendecomposition C1=f1−f0λ2λ1−λ2C2=f0λ1−f1λ1−λ2f0=C1+C2f1=C1λ1+C2λ2. Eigencoordinaces C1 and C2 can be computed either this way or in the course of partial fraction decomposition.
Identifying initial values with inputs
We have just got that our linear system produces non-causal sequence (the output is 0 for n < 0). This sequence is also a solution of the recurrence. It is curious that initial values, a0 and a1 can be identified with inputs. Let's first define left and right shift: R(y)=R(y0+y1z+y2z2+⋯)=0+y0z+y1z2+⋯=ay, L(y)=L(y0+y1z+y2z2+⋯)=y1+y2z+y3z2+⋯=(y−y0)/a, R(y)n=yy−1 L(y)n=yy+1 Therefore, yn=ayn−1+xn can be rewritten as z-transform Y=y(z)=azy(z)+x(z)=X/(1−az) where x is input at time t and output, our sequence, is identically zero if no input is applied. Same result can be obtained from eq yn+1=ayn+xn+1: (Y−y0)/z=aY+(x(z)−x0)/z⇒Y−y0=azY+(X−x0) ⇒Y=X+y0−x01−az==X+y−11−az=X1−az. The latter is because y−1=0 since we have causal sequences. For the second order system, yn=ayn−1+byn−2 we have y=a(zy+y−1)+b(z2y+zy−1+y−2)=ay−1+by−2+bzy−11−az−bz2=y0+bzy−11−az−bz2=0 since y−1=y−1=0 again and we again can add some input X to kick the sequence off zero. With y0=x0 and y1=ay0+x1⇒x1=y1−ay0 given, y=x1−az−bz2=x0+x1z1−az−bz2=y0+(y1−ay0)z1−az−bz2. y1−ay0=by−1, which we have before.In general, equation anyn+an−1yn−1+⋯+a0y0=bmxm+bm−1ym−1+b0x0 translates into Y=∑m0xizi∑n−10aizi=X⋅H where nominator X can be interpreted as either as input delta-pulses (in case of zero-state interpretation) or initial values (in case of zero-input interpretation).
See also What is the difference between zero-input and natural response.
No comments:
Post a Comment