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Signal Flow Graphs

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Signal Flow Graphs A Linear Time Invariant Discrete Time Systems can be made up from the elements { Storage, Scaling, Summation } Storage: (Delay, Register) – PowerPoint PPT presentation

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Title: Signal Flow Graphs


1
Signal Flow Graphs
  • Linear Time Invariant Discrete Time Systems can
    be made up from the elements 
  • Storage, Scaling, Summation  
  • Storage (Delay, Register)
  • Scaling (Weight, Product, Multiplier

2
Signal Flow Graphs
  •  Summation (Adder, Accumulator)
  •  
  • A linear system equation of the type considered
    so far, can be represented in terms of an
    interconnection of these elements
  • Conversely the system equation may be obtained
    from the interconnected components (structure).

3
Signal Flow Graphs
  • For example

4
Signal Flow Graphs
  • A SFG structure indicates the way through which
    the operations are to be carried out in an
    implementation.
  • In a LTID system, a structure can be
  • i) computable (All loops contain delays)
  • ii) non-computable (Some loops contain no
    delays)

5
Signal Flow Graphs
  • Transposition of SFG is the process of reversing
    the direction of flow on all transmission paths
    while keeping their transfer functions the same.
  • This entails
  • Multipliers replaced by multipliers of same value
  • Adders replaced by branching points
  • Branching points replaced by adders
  • For a single-input / output SFG the transpose SFG
    has the same transfer function overall, as the
    original.

6
Structures
  • STRUCTURES (The computational schemes for
    deriving the input / output relationships.)
  • For a given transfer function there are many
    realisation structures.
  • Each structure has different properties w.r.t.
  • i) Coefficient sensitivity
  • ii) Finite register computations

7
Signal Flow Graphs
  • Direct form 1 Consider the transfer function
  • So that
  • Set

8
Signal Flow Graphs
  • For which
  • Moreover

9
Signal Flow Graphs
  • For which

10
Signal Flow Graphs
  • This figure and the previous one can be combined
    by cascading to produce overall structure.
  • Simple structure but NOT used extensively in
    practice because its performance degrades rapidly
    due to finite register computation effects

11
Signal Flow Graphs
  • Canonical form Let
  • ie
  • and

12
Signal Flow Graphs
  • Hence SFG (n gt m)

13
Signal Flow Graphs
  • Direct form 2 Reduction in effects due to
    finite register can be achieved by factoring
    H(z) and cascading structures corresponding to
    factors
  • In general
  • with
  • or

14
Signal Flow Graphs
  • Parallel form Let
  • with Hi(z) as in cascade but a0i 0
  • With Transposition many more structures can be
    derived. Each will have different performance
    when implemented with finite precision

15
Signal Flow Graphs
  • Sensitivity Consider the effect of changing a
    multiplier on the transfer function
  • Set
  • With constraint

16
Signal Flow Graphs
  • Hence
  • And
  • thus

17
Signal Flow Graphs
  • Two-ports

18
Signal Flow Graphs
  • Example Complex Multiplier

19
Signal Flow Graphs
  • So that
  • Its SFD can be drawn as

20
Signal Flow Graphs
  • Special case
  • We have a rotation of t o by
    an angle
  • We can set so that
    and
  • This is the basis for designing
  • i) Oscillators
  • ii) Discrete Fourier Transforms (see later) 
  • iii) CORDIC operators in SONAR

21
Signal Flow Graphs
  • Example Oscillator
  • Consider and
    externally impose the constraint
  • So that
  • For oscillation

22
Signal Flow Graphs
  • Set
  • Hence

23
Signal Flow Graphs
  • With and ,
    the oscillation frequency
  • Set then
  • and
  • We obtain
  • Hence x1(n) and x2(n) correspond to two
    sinusoidal oscillations at 90? w.r.t. each other

24
Signal Flow Graphs
  • Alternative SFG with three real multipliers

25
Signal Flow Graphs
  • Example Oscillator
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