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ELEC 310 formulas

complex functions

z = x + jy, f(z) = u(x,y) + jv(x,y) (1)

transfer function, ratio of polynomials with poles and zeros

\begin{displaymath}H(z) = \frac{P(z)}{Q(z)}
\end{displaymath} (2)

z-transform

\begin{displaymath}H(z) = \sum_{k=0}^{\infty} h[k]z^{-k}
\end{displaymath} (3)

inverse z-transform, c encloses all poles of H(z) zk-1

\begin{displaymath}h[k] = \frac{1}{2\pi j}\int_c H(z) z^{k-1} dz
\end{displaymath} (4)

c encloses all poles of H(z) zk-1

geometric series

\begin{displaymath}\frac{C}{1-w} = C \sum_{k=0}^{\infty} w^k
\end{displaymath} (5)


\begin{displaymath}\frac{C}{(1-w)^2} = C \sum_{k=0}^{\infty} (k+1) w^k
= C \sum_{n=1}^{\infty} n w^{(n-1)}
\end{displaymath} (6)


\begin{displaymath}\frac{C}{(1-w)^3} = C \sum_{k=0}^{\infty} \frac{(k+1)(k+2)}{2} w^k =
C \sum_{n=2}^{\infty} \frac{n(n-1)}{2} w^{(n-2)}
\end{displaymath} (7)

basic inverse z-transform use geometric series with w=pz-1 to obtain transform pair

\begin{displaymath}H(z) = \frac{Cz}{z-p} = \frac{C}{1-pz^{-1}} \leftrightarrow h[k] = C p^k
\end{displaymath} (8)

Residue theorem

\begin{displaymath}\int_c H(z) dz = 2\pi j \sum_{res} H(z)
\end{displaymath} (9)

sum of all residues at poles inside c.

first order pole

\begin{displaymath}res_{z=a} F(z) = lim_{z\rightarrow a} [ (z-a)F(z) ]
\end{displaymath} (10)

if $F(z)=\frac{P(z)}{Q(z)}$, then

\begin{displaymath}res_{z=a} F(z) = \frac{P(a)}{Q'(a)}
\end{displaymath} (11)

second order pole

\begin{displaymath}res_{z=a} F(z) = lim_{z\rightarrow a} \frac{d}{dz}[ (z-a)^2F(z) ]
\end{displaymath} (12)

third order pole

\begin{displaymath}res_{z=a} F(z) = lim_{z\rightarrow a} \frac{1}{2} \frac{d^2}{dz^2}[ (z-a)^3F(z) ]
\end{displaymath} (13)

mth order pole

\begin{displaymath}res_{z=a} F(z) = lim_{z\rightarrow a} \frac{1}{m!} \frac{d^{(m-1)}}{dz^{(m-1)}}[ (z-a)^mF(z) ]
\end{displaymath} (14)

frequency response (amplitude and phase), sampling rate fs


\begin{displaymath}H(f) = H(z)\vert _{z=exp(j2\pi f/f_s)}, -f_s/2 < f < f_s/2
\end{displaymath} (15)

Discrete Fourier Transform (DFT) is frequency response sampled at N0 samples around the whole unit circle -fs/2<f<fs/2with frequency resolution (step size) f0=fs/N0


H[r] = $\displaystyle H(f)\vert _{f=r f_0 = r f_s/N_0},
0 \le r \le N_0-1$ (16)
  = $\displaystyle H(z)\vert _{z=exp(j2\pi f/f_s)}\vert _{f=r f_s/N_0}$ (17)
  = $\displaystyle H(z)\vert _{z=exp(j2\pi r/N_0)}$ (18)
  = $\displaystyle \sum_{k=0}^{N_0-1} h[k]z^{-k}\vert _{z=exp(j2\pi r/N_0)}$ (19)
  = $\displaystyle \sum_{k=0}^{N_0-1} h[k]exp(-j2\pi rk/N_0)$ (20)

inverse DFT


\begin{displaymath}h[k] = \frac{1}{N_0} \sum_{r=0}^{N_0-1} H[r]exp(+j2\pi rk/N_0)
\end{displaymath} (21)



 
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Peter Driessen
2001-03-25