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# ℓ_1 minimization proof

Module by: Mark A. Davenport. E-mail the author

Summary: 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, Lemma 4 is used in establishing the relationship between the RIP and the NSP as well as establishing results on 11 minimization in the context of sparse recovery in both the noise-free and noisy settings. In order to establish Lemma 4, we establish the following preliminary lemmas.

## Lemma 1

Suppose u,vu,v are orthogonal vectors. Then

u 2 + v 2 2 u + v 2 . u 2 + v 2 2 u + v 2 .
(1)

### Proof

We begin by defining the 2×12×1 vector w=u2,v2Tw=u2,v2T. By applying standard bounds on pp norms (Lemma 1 from "The RIP and the NSP") with K=2K=2, we have w12w2w12w2. From this we obtain

u 2 + v 2 2 u 2 2 + v 2 2 . u 2 + v 2 2 u 2 2 + v 2 2 .
(2)

Since uu and vv are orthogonal, u22+v22=u+v22u22+v22=u+v22, which yields the desired result.

## Lemma 2

If ΦΦ satisfies the restricted isometry property (RIP) of order 2K2K, then for any pair of vectors u,vΣKu,vΣK with disjoint support,

Φ u , Φ v δ 2 K u 2 v 2 . Φ u , Φ v δ 2 K u 2 v 2 .
(3)

### Proof

Suppose u,vΣKu,vΣK with disjoint support and that u2=v2=1.u2=v2=1. Then, u±vΣ2Ku±vΣ2K and u±v22=2u±v22=2. Using the RIP we have

2 ( 1 - δ 2 K ) Φ u ± Φ v 2 2 2 ( 1 + δ 2 K ) . 2 ( 1 - δ 2 K ) Φ u ± Φ v 2 2 2 ( 1 + δ 2 K ) .
(4)

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 Φ u , Φ v 1 4 Φ u + Φ v 2 2 - Φ u - Φ v 2 2 δ 2 K
(5)

establishes the lemma.

## Lemma 3

Let Λ0Λ0 be an arbitrary subset of {1,2,...,N}{1,2,...,N} such that |Λ0|K|Λ0|K. For any vector uRNuRN, define Λ1Λ1 as the index set corresponding to the KK largest entries of uΛ0cuΛ0c (in absolute value), Λ2Λ2 as the index set corresponding to the next KK largest entries, and so on. Then

j 2 u Λ j 2 u Λ 0 c 1 K . j 2 u Λ j 2 u Λ 0 c 1 K .
(6)

### Proof

We begin by observing that for j2j2,

u Λ j u Λ j - 1 1 K u Λ j u Λ j - 1 1 K
(7)

since the ΛjΛj sort uu to have decreasing magnitude. Applying standard bounds on pp 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 , 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 ,
(8)

proving the lemma.

We are now in a position to prove our main result. The key ideas in this proof follow from [1].

## Lemma 4

Suppose that ΦΦ satisfies the RIP of order 2K2K. Let Λ0Λ0 be an arbitrary subset of {1,2,...,N}{1,2,...,N} such that |Λ0|K|Λ0|K, and let hRNhRN be given. Define Λ1Λ1 as the index set corresponding to the KK entries of hΛ0chΛ0c with largest magnitude, and set Λ=Λ0Λ1Λ=Λ0Λ1. Then

h Λ 2 α h Λ 0 c 1 K + β Φ h Λ , Φ h h Λ 2 , h Λ 2 α h Λ 0 c 1 K + β Φ h Λ , Φ h h Λ 2 ,
(9)

where

α = 2 δ 2 K 1 - δ 2 K , β = 1 1 - δ 2 K . α = 2 δ 2 K 1 - δ 2 K , β = 1 1 - δ 2 K .
(10)

### Proof

Since hΛΣ2KhΛΣ2K, the lower bound on the RIP immediately yields

( 1 - δ 2 K ) h Λ 2 2 Φ h Λ 2 2 . ( 1 - δ 2 K ) h Λ 2 2 Φ h Λ 2 2 .
(11)

Define ΛjΛj as in Lemma 3, then since ΦhΛ=Φh-j2ΦhΛjΦhΛ=Φh-j2ΦhΛj, we can rewrite Equation 11 as

( 1 - δ 2 K ) h Λ 2 2 Φ h Λ , Φ h - Φ h Λ , j 2 Φ h Λ j . ( 1 - δ 2 K ) h Λ 2 2 Φ h Λ , Φ h - Φ h Λ , j 2 Φ h Λ j .
(12)

In order to bound the second term of Equation 12, we use Lemma 2, which implies that

Φ h Λ i , Φ h Λ j δ 2 K h Λ i 2 h Λ j 2 , Φ h Λ i , Φ h Λ j δ 2 K h Λ i 2 h Λ j 2 ,
(13)

for any i,ji,j. Furthermore, Lemma 1 yields hΛ02+hΛ122hΛ2hΛ02+hΛ122hΛ2. Substituting into Equation 13 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 . 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 .
(14)

From Lemma 3, 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 . Φ h Λ , j 2 Φ h Λ j 2 δ 2 K h Λ 2 h Λ 0 c 1 K .
(15)

Combining Equation 15 with Equation 12 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 , ( 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 ,
(16)

which yields the desired result upon rearranging.

## References

1. Candès, E. (2008). The restricted isometry property and its implications for compressed sensing. Comptes rendus de l'Académie des Sciences, Série I, 346(9-10), 589–592.

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