EE123 Digital Signal Processing. M. Lustig, EECS UC Berkeley

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EE123 Digital Signal Processing

Today Last time: DTFT - Ch 2 Today: Continue DTFT Z-Transform Ch. 3

Properties of the DTFT cont. Time-Freq Shifting/modulation: M. Lustig, EE123 UCB

M. Lustig, EE123 UCB

Frequency Response of LTI Systems Check response to a pure frequency: 0 LTI 0 0 0 M. Lustig, EE123 UCB

Frequency Response of LTI Systems Check response to a pure frequency: 0 LTI Output is the same pure frequency, scaled and phase-shifted! is an eigen function of LTI systems M. Lustig, EE123 UCB Recall eigen vectors satisfy:

Example 3 Frequency response of a causal moving average filter Q: What type of filter is it? A: Low-Pass 0 M n M. Lustig, EE123 UCB

Example 3 Cont. Frequency response of a causal moving average filter Same as example 1, only: Shifted by N, divided by M+1, M=2N M. Lustig, EE123 UCB

Example 3 Cont. Frequency response of a causal moving average filter Not a sinc! 1 M. Lustig, EE123 UCB

Example 4: Impulse Response of an Ideal Low-Pass Filter M. Lustig, EE123 UCB

Example 4 Impulse Response of an Ideal Low-Pass Filter M. Lustig, EE123 UCB

Example 4 Impulse Response of an Ideal Low-Pass Filter sampled sinc Non causal! Truncate and shift right to make causal M. Lustig, EE123 UCB

Example 4 Impulse Response of an Ideal Low-Pass Filter Non causal! Truncate and shift right to make causal How does it changes the frequency response? Truncation: property 2.9.7: Periodic convolution M. Lustig, EE123 UCB

Example 4 We get smearing of the frequency response We get rippling M. Lustig, EE123 UCB

The z-transform Used for: Analysis of LTI systems Solving difference equations Determining system stability Finding frequency response of stable systems

Eigen Functions of LTI Systems Consider an LTI system with impulse response h[n]: We already showed that are eigen-functions What if

Eigen Functions of LTI Systems x[n] = z n are also eigen-functions of LTI Systems H(z) is called a transfer function H(z) exists for larger class of h[n] than

The z Transform Since z=re jω

Region of Convergence (ROC) The ROC is a set of values of z for which the sum Converges.

Region of Convergence (ROC) Example 1: Right-sided sequence recall: So:

Region of Convergence (ROC) Example 2:

Region of Convergence (ROC) Example 3: Left sided sequence if a -1 z < 1, i.e, z < a then,

Region of Convergence (ROC) Expression is the same as Example 1! ROC = {z: z < a } is different The z-transform without ROC does not uniquely define a sequence!

Region of Convergence (ROC) Example 4: Same as example 2

Region of Convergence (ROC) Example 5: Example 6:

Region of Convergence (ROC) Example 7: Finite sequence Finite, always converges Zero cancels pole

Region of Convergence (ROC) finite sequence

Properties of ROC A ring or a disk in Z-plane, centered at the origin DTFT converges iff ROC includes the unit circle ROC can t contain poles

Properties of ROC For finite duration sequences, ROC is the entire z-plane, except possibly z=0, z=

Example: w[n] window -N N Z transform: What is the ROC? M. Lustig, EE123 UCB

Properties of the ROC For right-sided sequences: ROC extends outward from the outermost pole to infinity Examples 1,2 For left-sided: inwards from inner most pole to zero Example 3 For two-sided, ROC is a ring - or do not exist Examples 4,5,6

Several Properties of the Z-transform ROC at least ROCx ROCy

Inversion of the z-transform In general, by contour integration within the ROC Ways to avoid it: Inspection (known transforms) Properties of the z-transform Power series expansion Partial fraction expansion Residue theorem Most useful is the inverse of rational polynomials Why?

Cool DSP: Phase Vocoder, aka autotune Shifts the frequency and time domains of audio signals using phase information Uses the DFT, which we will discuss next time! https://www.youtube.com/watch?v=6fth0wrjox4