Finite Impulse Response (FIR) Digital Filters Digital filters are - - PowerPoint PPT Presentation

finite impulse response fir digital filters
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Finite Impulse Response (FIR) Digital Filters Digital filters are - - PowerPoint PPT Presentation

Finite Impulse Response (FIR) Digital Filters Digital filters are rapidly replacing classic analog filters. Programmable DSP with MAC can be used to implement digital filters. For high-bandwidth signal processing applications,


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SLIDE 1

Digital Kommunikationselektronik TNE027 Lecture 4 1

Finite Impulse Response (FIR) Digital Filters

  • Digital filters are rapidly replacing classic

analog filters.

  • Programmable DSP with MAC can be used

to implement digital filters.

  • For high-bandwidth signal processing

applications, FPGA technology can provide multiple MACs to achieve the desired thoughput.

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SLIDE 2

Digital Kommunikationselektronik TNE027 Lecture 4 2

  • FIR Theory

– An FIR with constant coefficient is an Linear Time-Invariant (LTI) filter. – The ouput of an FIR of order (or length) L, to an input time-series x[n], is given by a finite version of the convolution sum: y[n] = f[n]*x[n] = Σ f[k] x[n-k] where f[0] ≠ 0 through f[L-1] ≠ 0 are the filter’s L coefficients. They also correspond to the FIR’s impulse response.

L-1 k=0

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SLIDE 3

Digital Kommunikationselektronik TNE027 Lecture 4 3

  • LTI system expressed in the z-domain:

Y(z) = F(z) X(z) where F(z) is the FIR’s transfer function defined in z-domain by F(z) = Σ f[k] z–k The roots of polynomial F(z) define the zeros of the filter. FIRs are also called all zero filters.

k=0 L-1

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SLIDE 4

Digital Kommunikationselektronik TNE027 Lecture 4 4

Direct Form FIR Filter

Tapped delay line Tapped weight

  • Fig. 3.1.
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SLIDE 5

Digital Kommunikationselektronik TNE027 Lecture 4 5

FIR Filter with Transposed Structure

A variation of the direct FIR model is called the transposed FIR filter. It can be constructed from the direct form FIR filter by – Exchanging the input and output – Inverting the direction of signal flow – Substituting an adder by a fork, and vice versa

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SLIDE 6

Digital Kommunikationselektronik TNE027 Lecture 4 6

FIR Filter in the Transposed Structure

  • Fig. 3.3.

See Example 3.1: Programmable FIR Filter

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SLIDE 7

Digital Kommunikationselektronik TNE027 Lecture 4 7

  • The direct form FIR filter needs extra

pipeline registers between the adders to reduce the delay of the adder tree and to achieve high throughput.

  • The FIR filter with transposed structure has

registers between the adders and can achieve high throughput without adding any extra pineline registers.

Comparison of the two forms

  • f the FIR filter
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SLIDE 8

Digital Kommunikationselektronik TNE027 Lecture 4 8

Symmetry in FIR Filters

  • Define the center point of an odd-order

FIR’s impulse response as the 0th sample: F(z) = Σ f[k] z–k

(An even-order FIR can be similarly defined.)

  • Linear-phase FIR filter

– Linear-phase is achieved if the filter is symmetric or antisymmetric. See Table 3.1.

k=(L-1)/2 k=-(L-1)/2

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SLIDE 9

Digital Kommunikationselektronik TNE027 Lecture 4 9

  • Fig. 3.5. L’ = L/2, where L is an even number.

Linear-phase even-order filter with reduced number of multipliers

f[L’-1] f[L’-2]

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SLIDE 10

Digital Kommunikationselektronik TNE027 Lecture 4 10

Constant Coefficient FIR Design

  • There are only a few applications, e.g.,

adaptive filters, where we need a general programmable filter.

  • In many applications, the filters are Linear

Time Invariant (LTI) and the coefficients do not change over time.

  • The hardware effort can be reduced for

constant coefficient FIR.

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SLIDE 11

Digital Kommunikationselektronik TNE027 Lecture 4 11

Direct FIR implementation

  • In a practical situation, the FIR coefficients are
  • btained from a computer design tool and

presented to the designer as floating point numbers.

  • The performance of a fixed-point FIR, based on

the floating-point coefficients, should be verified using simulation or algebraic analysis to ensure that design specifications remain satisfied.

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SLIDE 12

Digital Kommunikationselektronik TNE027 Lecture 4 12

  • Dynamic range overflow should be

avoided.

  • The worst-case dynamic range growth G of

an Lth- order FIR is G ≤ log2(Σ |f[k]|) See Example 3.2: Four-tap direct FIR filter.

L-1 k=0

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SLIDE 13

Digital Kommunikationselektronik TNE027 Lecture 4 13

Improve the direct FIR design

  • 1. Realize each filter coefficient with an
  • ptimal CSD code.
  • 2. Increase effective multiplier speed by

pipelining.

  • 3. For FIR with symmetric coefficients, the

number of multipliers can be reduced. See Table 3.3 and Example 3.3.

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SLIDE 14

Digital Kommunikationselektronik TNE027 Lecture 4 14

Rephasing pipelined multiplier in FIR filter Add a positive delay f[n]=z d f[n] z -d

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SLIDE 15

Digital Kommunikationselektronik TNE027 Lecture 4 15

FIR Filter with Transposed Structure

  • If the transposed filter has constant

coefficients, two improved designs should be considered:

– Multiple use of the repeated coefficients using the reduced adder graph (RAG) algorithm – Pipeline adders

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SLIDE 16

Digital Kommunikationselektronik TNE027 Lecture 4 16

Reduced Adder Graph

Algorithm 3.4: Reduced Adder Graph

a) Remove the sign of the coefficient. b) Remove all coefficients and factors that are a power of two. c) Realize all cost “1” coefficients. d) Use cost “1” coefficients in building the multiplier of higher cost. (Use Table 2.3.) See Example 3.5.

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SLIDE 17

Digital Kommunikationselektronik TNE027 Lecture 4 17

Reduced Adder Graph for F6 Half-band Filter

  • Fig. 3.11. Realization of F6 using RAG algorithm
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SLIDE 18

Digital Kommunikationselektronik TNE027 Lecture 4 18

FIR Filter Using Distributed Arithmetic

  • Distributed Arithmetic Using Logic Cells

See Example 3.6: Distributed Arithmetic Filter as State Machine. – Logic cells are used to implement small look- up tables for low-order filters. – The outputs of a collection of low-order filters can be added together to define the output of a high-order FIR. See Example 3.7: Five-input DA Table.

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SLIDE 19

Digital Kommunikationselektronik TNE027 Lecture 4 19

  • DA Using Embedded Array Blocks

– It is not economical to use the 2-kbit EABs for a short FIR filter, mainly because the number of available EABs is limited. – The maximum registered speed of an EAB is 76 MHz, and an LC table implementation may be faster for a short FIR filter. – For long filters, EABs have registered throughput at a constant 76 MHz and routing effort is reduced. See Example 3.8: Distributed Arithmetic Filter using EABs.

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SLIDE 20

Digital Kommunikationselektronik TNE027 Lecture 4 20

  • Fig. 3.16:

Parallel implementation

  • f a distributed

arithmetic FIR filter Example 3.10: Loop Unrolling for DA FIR Filter