• No results found

The sum of two maximal monotone operator is of type FPV

N/A
N/A
Protected

Academic year: 2020

Share "The sum of two maximal monotone operator is of type FPV"

Copied!
5
0
0

Loading.... (view fulltext now)

Full text

(1)

University of Mazandaran, Iran http://cjms.journals.umz.ac.ir ISSN: 1735-0611 CJMS.5(1)(2016), 17-21

The sum of two maximal monotone operator is of type FPV

Vahid Dadashi 1 and Mahya Hosseini 1

1 Department of Mathematics, Sari Branch, Islamic Azad University,

Sari, Iran

Abstract.In this paper, we studied maximal monotonicity of type FPV for sum of two maximal monotone operators of type FPV and the obtained results improve and complete the corresponding re-sults of this filed.

Keywords: Maximal monotone operator, Maximal monotone op-erator of type FPV, Subdifferential.

2000 Mathematics subject classification: 47H05, 47H04, 46N10.

1. Introduction and Preliminaries

Throughout this paper, we assume that X is a real Banach space with normk.k, that X∗ is the continuous dual ofX, and thatX and X∗ are paired byh., .i. LetA:X⇒X∗ be a set-valued operator(also known as multifunction) from X to X∗, i.e., for every x ∈X, Ax⊆ X∗, and let GphA={(x, x∗)∈X×X∗|x∗ ∈Ax} be the graph ofA.

Definition 1.1. A is monotone if

hx−y, x∗−y∗i ≥0 ∀(x, x∗)∈GphA ∀(y, y∗)∈GphA,

and maximal monotone ifAis monotone andAhas no proper monotone extension (in the sense of graph inclusion).

1Corresponding author: [email protected]

Received: 07 December 2014 Revised: 31 October 2015 Accepted: 05 January 2016

(2)

Definition 1.2. Let A:X ⇒ X∗ be maximal monotone. A is of type FPV if for every open convex setU ⊂X such thatU ∩DomA6=∅, the implication

x∈U and (x, x∗) |is monotonically related to GphA∩U ×X∗ ⇒ (x, x∗)∈GphA

holds.

Monotone operators have proven to be a key class of objects in modern Optimization and Analysis; see, e.g., the books [1, 2, 3, 4, 8, 12] and the references there in. We adopt standard notation used in these books: DomA={x∈X |Ax6=∅}is the domain ofA. Given a subsetC ofX, intC is the interior ofC, andC is the norm closure ofC. The indicator function of C, written as ιC, is defined at x∈X by

ιC(x) =

0 x∈C ∞ x /∈C.

We set dist(x, C) = infc∈Ckx −ck, for x ∈ X. If D ⊆ X, we set

C −D = {x −y | x ∈ C, y ∈ D}. For every x ∈ X, the normal cone operator of C atx is defined byNC(x) = {x∗ ∈ X∗ | supc∈Chc−

x, x∗i ≤ 0}, if x ∈ C; and NC(x) =∅, if x /∈ C. For x, y ∈ X, we set [x, y] = {tx+ (1−t)y | 0 ≤ t ≤ 1}. Given f : X →]− ∞,+∞], we set domf =f−1(R) and f∗:X∗ →[−∞,+∞] :x∗ 7→supx∈X(hx, x∗i −

f(x)) is the Fenchel conjugate of f. iff is convex and domf 6=∅, then ∂f : X ⇒ X∗ : x 7→ {x∗ ∈ X∗ | ( ∀y ∈ X)hy−x, x∗i+f(x) ≤ f(y)} is the subdifferential operator of f. Finally, the open unit ball in X is denoted byBX ={x∈X | kxk<1}.

LetAandBbe maximal monotone operators fromXtoX∗. Clearly, the sum operatorA+B :X X∗ :x7→Ax+Bx={a∗+b∗ |a∗ ∈Ax, b∗ ∈ Bx} is monotone. Rockafellars guarantees maximal monotonicity of A+Bunder Rockafellars constraint qualification DomA∩intDomB 6=∅ whenX is reflexive- this result is often referred to as the sum theorem.

Theorem 1.3. [12] Letf :X →]− ∞,+∞]be a convex and lower semi-continuous function. Then f is continuous at the points of int domf.

Theorem 1.4. [7] Let f : X →]− ∞,+∞] be a proper, convex and lower semicontinuous function. Then∂f is maximal monotone.

Theorem 1.5. (Rockafellar)[6, 8, 12]Letf, g:X →]−∞,+∞]be proper convex functions. Assume that there exists a point x0 ∈domf∩domg

such thatg is continuous atx0. Then ∂(f+g) =∂f+∂g.

(3)

Theorem 1.7. (Heisler)[5] Let A, B :X ⇒ X∗ be maximal monotone with full domain. Then A+B is maximal monotone.

Now we cite some results on maximal monotone operators of type FPV

Theorem 1.8. (Simons and Verona- Verona)[8, 9] Let A:X⇒X∗ be a maximal monotone. Suppose that for every closed subsetC of X with DomA∩intC 6= ∅, the operator A+NC is maximal monotone. Then

A is of type FPV.

Corollary 1.9. [11] Let A : X ⇒ X∗ be maximal monotone of type FPV with convex domain, let C be a nonempty closed convex subset of X, and suppose thatDomA∩intC 6=∅. Then A+NC is of type FPV.

Theorem 1.10. [11] Let A, B : X ⇒ X∗ be maximal monotone with DomA∩int DomB 6=∅. Assume that A+NDomB is maximal monotone of type FPV, and DomA∩DomB ⊆DomB. Then A+B is maximal monotone.

Theorem 1.11. [11] Let A : X ⇒ X∗ be maximal monotone of type FPV, and let B : X ⇒ X∗ be maximal monotone with full domain. ThenA+B is maximal monotone.

Theorem 1.12. [11] Let A : X ⇒ X∗ be maximal monotone of type FPV with convex domain, and let B : X ⇒ X∗ be maximal monotone with DomA∩int DomB 6=∅. Assume that DomA∩DomB ⊆DomB. ThenA+B is maximal monotone .

2. Main results

Theorem 2.1. Let A : X ⇒ X∗ be maximal monotone of type FPV with convex domain, and let B :X ⇒ X∗ be maximal monotone with DomA∩int DomB 6=∅. Assume thatDomA∩DomB⊆DomB. Then A+B is maximal monotone of type FPV.

Proof. By Theorem 1.12A+Bis maximal monotone and we it is proved thatA+B is of type FPV. Let Dbe a nonempty closed convex subset of X, and suppose that Dom(A+B)∩intD 6= ∅. Let x1 ∈ DomA∩

int DomB andx2∈Dom(A+B)∩intD. Thus, there existsδ >0 such

that x1+δBX ⊂ DomB and x2+δBX ⊂ D. Then for small enough

λ∈]0,1[, we have x2 +λ(x1−x2) + 12δBX ⊂D. Clearly, x2+λ(x1−

x2) +λδBX ⊂ DomB. Thus x2 +λ(x1−x2) + λδ2 BX ⊂ DomB∩D. Since DomA is convex,x2+λ(x1−x2)∈DomAand x2+λ(x1−x2)∈

(4)

of type FPV. Now, by Theorem 1.10, (A+ND)+Bis maximal monotone and hence, by Theorem 1.8,A+B is of type FPV.

Corollary 2.2. Let A, B : X ⇒ X∗ be maximal monotone with full domain. Then A+B is maximal monotone of type FPV.

Proof. By Theorem 1.7A+B is maximal monotone and clearly, all con-ditions of Theorem 2.1 are satisfied. ThenA+B is maximal monotone

of type FPV.

Corollary 2.3. Let A : X ⇒ X∗ be maximal monotone of type FPV with convex domain, letf :X →]− ∞,+∞]be proper, convex and lower semicontinuous with DomA∩intDom∂f 6= ∅. Assume that DomA∩ Dom∂f ⊆Dom∂f. Then A+∂f is maximal monotone of type FPV.

Proof. By Theorem 1.4, ∂f is maximal monotone. The conclusion fol-lows from assumptions and Theorem 2.1

Corollary 2.4. [11] Let A : X ⇒ X∗ be maximal monotone of type FPV with convex domain, let C be a nonempty closed convex subset of X, and suppose thatDomA∩intC 6=∅. Then A+NC is of type FPV.

Proof. Let f =ιC, then all conditions of Corollary 2.3 are satisfied and

henceA+NC is of type FPV.

Theorem 2.5. Let A : X ⇒ X∗ be maximal monotone of type FPV with convex domain, and let B :X ⇒ X∗ be maximal monotone with full domain. Then A+B is maximal monotone of type FPV.

Proof. By corollary 1.11, A+B is maximal monotone. Let D be a nonempty closed convex subset of X, and suppose that Dom(A+B)∩ intD6=∅. By Theorem 1.9, (A+ND)+NDomB =A+ND+NX =A+ND is maximal monotone of type FPV. Then Theorem 1.10 implies that (A+ND) +B = (A+B) +ND is maximal monotone. Now, by Theorem

1.8, A+B is of type FPV.

3. Acknowledgment

Vahid Dadashi is supported by the Sari Branch, Islamic Azad Uni-versity.

References

[1] J.M. Borwein and J.D. Vanderwerff, Convex Functions, Cambridge Uni-versity Press, 2010.

[2] R.S. Burachik and A.N. Iusem, Set-Valued Mappings and Enlargements of Monotone Operators, Springer-Verlag, 2008.

(5)

[4] R.R. Phelps, Convex Functions, Monotone Operators and Differentiability, 2nd Edition, Springer-Verlag, 1993.

[5] R.R. Phelps, Lectures on maximal monotone operators, Extracta Mathe-maticae.12(1997), 193–230.

[6] R.T. Rockafellar, Extension of Fenchels duality theorem for convex func-tions,Duke Mathematical Journal, 33(1966), 81–89.

[7] R. T. Rockafellar, On the maximal monotonicity of subdifferential map-pings.Pacific J. Math., 33(1)(1970), 209–216.

[8] S. Simons , From Hohn- Banach to Monotonicity, Springer- Verlag, 2008. [9] A. Verona and M.E.Verona, Regular maximal monotone operators,

Set-Valued Analysis,6(1998), 303–312.

[10] A. Verona and M.E.Verona, Regular maximal monotone operators and the sum theorm, Journal of Convex Analysis7(2000), 115–128.

[11] L. Yao, The sum of a maximal monotone operator of type(FPV) and a maximal monotone operator with full domain is maximal monotone, 74(17)(2011), 6144–6152.

References

Related documents

A study on medical students, residents, and graduate stu- dents at four Canadian schools of medicine re- vealed significant differences between the three groups in the nature

In order to gain insight into molecular networks affected by aging, we performed Gene Ontology (GO) analysis, based on 5237 protein groups quantified by at least two unique

Using a large rep- licate data set we found that signal variability in microar- ray data is in fact probe set-specific, and developed a novel method to integrate a priori

Left: age of first khat intake among lifetime chewers in patients with psychotic symptoms (35) and case controls (23); right: amount of khat use (in 'bundles' per day) in the

The volume Internet and Surveillance: The Challenges of Web 2.0 and Social Media , edited by Christian Fuchs, Kees Boersma, Anders Albrechtslund and Marisol Sandoval, can in

Using genotype data from 26 global populations grouped into five super-populations, (1) we compared the genetic risk burden and frequency distributions of birthweight- lowering

(A, B) The mean (±SD) was plotted of the distribution of the AD (A) and NAD (B) patients in the Paris, Lille, and Montpellier cohorts and across the four classes based on the

Levels of miR-181a transcripts (normalized to miR-142 transcript levels) were lower in NCD4lo cells compared to NCD4hi cells (Figure 8C), further suggesting that because of