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Review of Filter Design

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1 Review of Filter Design
MP574 April 14, 2006

2 Difference Equation Implementation
Shift theorem of z-transform:

3 Difference Equation Implementation
Shift theorem of z-transform: FIR

4 Filter Design: IIR vs. FIR
Rules of thumb: Use IIR when the only important requirements are sharp cutoff and high throughput Use FIR in any application where linear phase is required

5 FIR Filter Design Phase Delay 4 Types of Linear Phase Tp = -q(w)/w
Tg= -dq(w)/dw 4 Types of Linear Phase Positive symmetry, odd number of coefficients Tp = (N-1)/2 Tsample Positive symmetry, even number of coefficients Tp = (N/2-1/2)Tsample Zero at w = p Negative, odd Negative, even Tg = (N-1-p)/2 Tsample p/2 phase shift Zero at w = 0

6 Design Steps Filter specification Coefficient calculation Realization
dp peak passband deviation (or ripple) ds stopband deviation fp passband edge frequency fs stopband edge frequency Fs sampling frequency Coefficient calculation Coefficients of H(z) Realization Implementation

7 Matlab: fdatool

8 IIR: Chebyshev Type II Order 10

9 IIR: Chebyshev Type II Order 10

10 FIR: Hamming Window Order 30

11 FIR: Hamming Window Order 30

12 Sptool Import

13 Sptool Apply Filter

14 Summary of Filter Design
Range of polynomial forms of different orders IIR converges to specifications more rapidly Non-linear phase Can be unstable in implementation FIR most commonly used for medical implementations Linear phase: signal preserved without distortion More constraints require higher order fits Stable and robust to quantization errors Matlab tools for filter design Take some time to familiarize yourself with them

15 Extension to 2D Parks-McClellan Transformation
Step 1: Translate specifications of H(w1,w2) to H(w) Step 2: Design 1D filter H(w) Step 3: Map to 2D frequency space cosw = - ½ + ½ cosw1 + ½ cosw2 + ½ cosw1 cosw2 = T(w1,w2) - Step 4: determine h(n1,n2) by 2D FT.

16 Hamming Window Example

17 Hamming Window Example
>> w1 = -pi:0.01:pi; >> w2 = -pi:0.01:pi; >> [W1,W2] = meshgrid(w1,w2); >> H_2d = *( *cos(W1)+0.5.*cos(W2)+0.5.*cos(W1).*cos(W2)); >>figure;mesh(H_2d) filter2()

18 2D FIR Filter Design, Parks-McClellan

19 “firdemo”

20 Improvement After Affine Registration to Mask Frame

21 T1 fitting There are two slices only one of which contains the lesion (arrow)


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