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In this module we prove one of the core lemmas that is used throughout this course to establish results regarding ℓ_1 minimization.

We now establish one of the core lemmas that we will use throughout this course . Specifically, [link] is used in establishing the relationship between the RIP and the NSP as well as establishing results on 1 minimization in the context of sparse recovery in both the noise-free and noisy settings. In order to establish [link] , we establish the following preliminary lemmas.

Suppose u , v are orthogonal vectors. Then

u 2 + v 2 2 u + v 2 .

We begin by defining the 2 × 1 vector w = u 2 , v 2 T . By applying standard bounds on p norms (Lemma 1 from "The RIP and the NSP" ) with K = 2 , we have w 1 2 w 2 . From this we obtain

u 2 + v 2 2 u 2 2 + v 2 2 .

Since u and v are orthogonal, u 2 2 + v 2 2 = u + v 2 2 , which yields the desired result.

If Φ satisfies the restricted isometry property (RIP) of order 2 K , then for any pair of vectors u , v Σ K with disjoint support,

Φ u , Φ v δ 2 K u 2 v 2 .

Suppose u , v Σ K with disjoint support and that u 2 = v 2 = 1 . Then, u ± v Σ 2 K and u ± v 2 2 = 2 . Using the RIP we have

2 ( 1 - δ 2 K ) Φ u ± Φ v 2 2 2 ( 1 + δ 2 K ) .

Finally, applying the parallelogram identity

Φ u , Φ v 1 4 Φ u + Φ v 2 2 - Φ u - Φ v 2 2 δ 2 K

establishes the lemma.

Let Λ 0 be an arbitrary subset of { 1 , 2 , ... , N } such that | Λ 0 | K . For any vector u R N , define Λ 1 as the index set corresponding to the K largest entries of u Λ 0 c (in absolute value), Λ 2 as the index set corresponding to the next K largest entries, and so on. Then

j 2 u Λ j 2 u Λ 0 c 1 K .

We begin by observing that for j 2 ,

u Λ j u Λ j - 1 1 K

since the Λ j sort u to have decreasing magnitude. Applying standard bounds on p norms (Lemma 1 from "The RIP and the NSP" ) we have

j 2 u Λ j 2 K j 2 u Λ j 1 K j 1 u Λ j 1 = u Λ 0 c 1 K ,

proving the lemma.

We are now in a position to prove our main result. The key ideas in this proof follow from  [link] .

Suppose that Φ satisfies the RIP of order 2 K . Let Λ 0 be an arbitrary subset of { 1 , 2 , ... , N } such that | Λ 0 | K , and let h R N be given. Define Λ 1 as the index set corresponding to the K entries of h Λ 0 c with largest magnitude, and set Λ = Λ 0 Λ 1 . Then

h Λ 2 α h Λ 0 c 1 K + β Φ h Λ , Φ h h Λ 2 ,

where

α = 2 δ 2 K 1 - δ 2 K , β = 1 1 - δ 2 K .

Since h Λ Σ 2 K , the lower bound on the RIP immediately yields

( 1 - δ 2 K ) h Λ 2 2 Φ h Λ 2 2 .

Define Λ j as in [link] , then since Φ h Λ = Φ h - j 2 Φ h Λ j , we can rewrite [link] as

( 1 - δ 2 K ) h Λ 2 2 Φ h Λ , Φ h - Φ h Λ , j 2 Φ h Λ j .

In order to bound the second term of [link] , we use [link] , which implies that

Φ h Λ i , Φ h Λ j δ 2 K h Λ i 2 h Λ j 2 ,

for any i , j . Furthermore, [link] yields h Λ 0 2 + h Λ 1 2 2 h Λ 2 . Substituting into [link] we obtain

Φ h Λ , j 2 Φ h Λ j = j 2 Φ h Λ 0 , Φ h Λ j + j 2 Φ h Λ 1 , Φ h Λ j j 2 Φ h Λ 0 , Φ h Λ j + j 2 Φ h Λ 1 , Φ h Λ j δ 2 K h Λ 0 2 j 2 h Λ j 2 + δ 2 K h Λ 1 2 j 2 h Λ j 2 2 δ 2 K h Λ 2 j 2 h Λ j 2 .

From [link] , this reduces to

Φ h Λ , j 2 Φ h Λ j 2 δ 2 K h Λ 2 h Λ 0 c 1 K .

Combining [link] with [link] we obtain

( 1 - δ 2 K ) h Λ 2 2 Φ h Λ , Φ h - Φ h Λ , j 2 Φ h Λ j Φ h Λ , Φ h + Φ h Λ , j 2 Φ h Λ j Φ h Λ , Φ h + 2 δ 2 K h Λ 2 h Λ 0 c 1 K ,

which yields the desired result upon rearranging.

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Source:  OpenStax, Introduction to compressive sensing. OpenStax CNX. Mar 12, 2015 Download for free at http://legacy.cnx.org/content/col11355/1.4
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