2015
DOI: 10.5937/kgjmath1502217k
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Compactness of matrix operators on some sequence spaces derived by Fibonacci numbers

Abstract: Abstract. In this paper, we apply the Hausdorff measure of noncompactness to obtain the necessary and sufficient conditions for certain matrix operators on the Fibonacci difference sequence spaces p ( F ) and ∞ ( F ) to be compact, where 1 ≤ p < ∞.

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Cited by 20 publications
(12 citation statements)
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“…Kara defined the Fibonacci difference matrix trueF^=false(truef^nkfalse) by f^nk=fn+1fn,k=n1fnfn+1,k=n0,0k<n13.0235ptor3.0235ptk>n and introduced some new difference sequence spaces by using this matrix. For more applications of Fibonacci numbers in sequence spaces, one can see previous works …”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Kara defined the Fibonacci difference matrix trueF^=false(truef^nkfalse) by f^nk=fn+1fn,k=n1fnfn+1,k=n0,0k<n13.0235ptor3.0235ptk>n and introduced some new difference sequence spaces by using this matrix. For more applications of Fibonacci numbers in sequence spaces, one can see previous works …”
Section: Introductionmentioning
confidence: 99%
“…For more applications of Fibonacci numbers in sequence spaces, one can see previous works. [9][10][11][12][13][14][15][16][17][18][19][20] As an application of Fibonacci numbers into infinite regular matrices, Kara and Başarır 21 have defined a new regular matrix F = (f nk ) by using the Fibonacci numbers as follows:…”
Section: Introductionmentioning
confidence: 99%
“…Since then many authors studied and generalized Fibonacci difference sequence spaces. We refer to [11,13,14,16,[30][31][32][33][34] for relevant studies. Motivated by the above studies, we introduced generalized Fibonacci difference operator by the composition of the Fibonacci band matrix F and the triple band matrix B(x, y, z).…”
Section: Fibonacci Sequence Spacesmentioning
confidence: 99%
“…For further details on the normed spaces derived by the Fibonacci matrix, we refer the readers to the recent papers [4,6,[8][9][10].…”
Section: Corollary 12 Let W = (W N ) ∞mentioning
confidence: 99%