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Now we consider another way (actually two related ways) to measure optimality of an encoder/decoder pair.

  • Instance optimality. Suppose we are in N ℝ^N with an n × N n times N measurement matrix Φ Φ and a decoder Δ Δ . Recall that
    σ k ( x ) X : = inf z : # z k x z X .
    We say that the encoding/decoding strategy Φ , Δ Φ ,Δ is instance optimal of order k k with constant C 0 C_0 if
    x Δ Φ ( x ) X C 0 σ k ( x ) X
    for all x N x in ℝ^N . (Note that we are no longer restricting x x to a class K K .) Better Φ Φ ’s have larger k k for which this holds. The name “instance optimal” indicates that the encoding/decoding performance depends on each instance of x x .
  • Mixed-norm instance optimality (MNIO). Let q < p q<p . The encoder/decoder pair Φ , Δ Φ ,Δ is MNIO for p , q , k p ,q ,k , and C 0 C_0 if
    x Δ Φ ( x ) p N C 0 σ k ( x ) q N k 1 q 1 p .
    Cases of interest include asking whether
    x Δ Φ ( x ) 2 N C 0 σ k ( x ) 1 N .
    and whether
    x Δ Φ ( x ) 2 N C 0 σ k ( x ) 1 N k .

Let’s focus on instance optimality. It would be interesting to know whether a given Φ Φ satisfies this property. To answer this question, we state an equivalent condition to instance optimality.

Consider the statements

  • Φ , Δ Φ ,Δ is instance optimal of order k k on X X .
  • Φ Φ has the following nullspace property (NSP): η X C 1 η T c X η N ( Φ ) , # T k .
  • η X C 1 σ k ( η ) X η N ( Φ ) .
  • η T X C 1 η T c X η N ( Φ ) , # T k .

Then (b) and (c) are equivalent with the same constant; (d) is equvalent to (b) and (c) but with a different constant. Also (a) with a value k k implies (b) with the same k k , and (b) with a value 2 k 2 k implies (a) with a value k k .

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Source:  OpenStax, Compressive sensing. OpenStax CNX. Sep 21, 2007 Download for free at http://cnx.org/content/col10458/1.1
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