Degenerate Bernstein Polynomials Associated with the Probability Distribution

Degenerate Bernstein Polynomials Associated with the Probability Distribution

DEGENERATE BERNSTEIN POLYNOMIALS TAEKYUN KIM AND DAE SAN KIM Abstract. Here we consider the degenerate Bernstein polynomials as a de- generate version of Bernstein polynomials, which are motivated by Simsek’s recent work ’Generating functions for unification of the multidimensional Bernstein polynomials and their applications’([15,16]) and Carlitz’s degen- erate Bernoulli polynomials. We derived thier generating function, sym- metric identities, recurrence relations, and some connections with general- ized falling factorial polynomials, higher-order degenerate Bernoulli poly- nomials and degenerate Stirling numbers of the second kind. 1. Introduction For λ ∈ R, the degenerate Bernoulli polynomials of order k are defined by L. Cartliz as k ∞ n t x t λ (k) 1 (1 + λt) = βn,λ , (see [4, 5]). (1.1) λ n! (1 + λt) − 1 n=0 X (k) (k) Note that limλ→0 βn,λ(x) = Bn (x) are the ordinary Bernoulli polynomials of order k given by ∞ t k tn ext = B(k)(x) , (see [1, 12, 13]). et − 1 n n! n=0 X It is known that the Stirling number of the second kind is defined as n n x = S2(n,l)(x)l, (see [2, 4, 8, 10]), (1.2) l X=0 arXiv:1806.06379v1 [math.NT] 17 Jun 2018 where (x)l = x(x − 1) ··· (x − l + 1), (l ≥ 1), (x)0 = 1. For λ ∈ R, the (x)n,λ is defined as (x)0,λ =1, (x)n,λ = x(x − λ)(x − 2λ) ··· (x − (n − 1)λ), (n ≥ 1) (1.3) 2010 Mathematics Subject Classification. 11B83. Key words and phrases. degenerate Bernstein polnomials. 1 2 TAEKYUNKIMANDDAESANKIM x In [8,9,10], n λ is defined as x (x)n,λ x(x − λ) ··· (x − (n − 1)λ) x = = , (n ≥ 1), =1. (1.4) n n! n! 0 λ λ Thus, by (1.4), we get ∞ x x (1 + λt) λ = tn, (see [7]). (1.5) n n=0 λ X From (1.5), we note that n y x x + y = , (n ≥ 0). (1.6) m n − m n m=0 λ λ λ X The degenerate Stirling numbers of the second kind are defined by ∞ n 1 1 k t λ (1 + λt) − 1 = S2,λ(n, k) , (k ≥ 0), (see [7, 8]). (1.7) k! n! n=k X By (1.7), we easily get lim S2,λ(n, k)= S2(n, k), (n ≥ k ≥ 0), (see [8, 10]). λ→0 In this paper, we use the following notation. n n n (x ⊕λ y) = (x)k,λ(y)n−k,λ, (n ≥ 0). (1.8) k k X=0 The Bernstein polynomials of degree n is defined by n − B (x)= xk(1 − x)n k, (n ≥ k ≥ 0), (see [6, 11, 17]). (1.9) k,n k Let C[0, 1] be the space of continuous functions on [0, 1]. The Bernstein operator of order n for f is given by n n k n k n−k k Bn(f|x)= f( ) x (1 − x) = f( )Bk,n(x), (1.10) n k n k k X=0 X=0 where n ∈ N ∪{0} and f ∈ C[0, 1], (see [3,6,14]). A Bernoulli trial involves performing a random experiment and noting whether a particular event A occurs. The outcome of Bernoulli trial is said to be ”suc- cess” if A occurs and a ”failure” otherwise. The probability Pn(k) of k successes in n independent Bernoulli trials is given by the binomial probability law: n − P (k)= pk(1 − p)n k, for k =0, 1, 2, ··· , n k From the definition of Bernstein polynomials we note that Bernstein basis is probability mass of binomial distribution with parameter (n, x = p). DEGENERATEBERNSTEINPOLYNOMIALS 3 Let us assume that the probability of success in an experiment is p. We wondered if we can say the probability of success in the nineth trial is still p after failing eight times in a ten trial experiment. Because there’s a psychological burden to be successful. It seems plausible that the probability is less than p. This speculation mo- tivated the study of the degenerate Bernstein polynomials associated with the probability distribution. In this paper, we consider the degenerate Bernstein polynomials as a degen- erate version of Bernstein polynomials. We derive thier generating function, symmetric identities, recurrence relations, and some connections with general- ized falling factorial polynomials, higher-order degenerate Bernoulli polynomials and degenerate Stirling numbers of the second kind. 2. Degenerate Bernstein polynomials For λ ∈ R and k,n ∈ N ∪{0}, with k ≤ n, we define the degenerate Bernstein polynomials of degree n which are given by n B (x|λ)= (x) (1 − x) − , (x ∈ [0, 1]). (2.1) k,n k k,λ n k,λ Note that limλ→0 Bk,n(x|λ) = Bk,n(x), (0 ≤ k ≤ n). From (2.1), we derive the generating function of Bk,n(x|λ), which are given by ∞ ∞ tn n tn Bk,n(x|λ) = (x)k,λ(1 − x)n−k,λ n! k n! n=k n=k X X ∞ (x)k,λ 1 n = (1 − x)n−k,λt k! (n − k)! n=k X∞ (x) (1 − x) = k,λ n,λ tn+k (2.2) k! n! n=0 X∞ (x) 1 − x = k,λ tk tn k! n n=0 λ X (x)k,λ 1−x = tk(1 + λt) λ . k! Therefore, by (2.2), we obtain the following theorem. Theorem 2.1. For x ∈ [0, 1] and k =0, 1, 2, ··· , we have ∞ n 1 1−x t (x) tk(1 + λt) λ = B (x|λ) . k! k,λ k,n n! n k X= 4 TAEKYUNKIMANDDAESANKIM From (2.1), we note that n n Bk,n(x|λ)= (x)k,λ(1 − x)n−k,λ = (x)k,λ(1 − x)n−k,λ. (2.3) k n − k By replacing x by 1 − x, we get n B (1 − x|λ)= (1 − x) (x) − = B − (x|λ), (2.4) k,n n − k k,λ n k,λ n k,n where n, k ∈ N ∪{0}, with 0 ≤ k ≤ n. Therefore, by (2.4), we obtain the following theorem. Theorem 2.2. ( Symmetric identities) For n, k ∈ N ∪{0}, with k ≤ n, and x ∈ [0, 1], we have Bn−k,n(x|λ)= Bk,n(1 − x|λ). Now, we observe that n − k k +1 B (x|λ)+ B (x|λ) n k,n n k+1,n n − k n k +1 n = (x)k,λ(1 − x)n−k,λ + (x)k ,λ(1 − x)n−k− ,λ n k n k +1 +1 1 (n − 1)! (n − 1)! = (x)k,λ(1 − x)n−k,λ + (x)k ,λ(1 − x)n−k− ,λ k!(n − k − 1)! k!(n − k − 1)! +1 1 = (1 − x − (n − k − 1)λ)Bk,n−1(x|λ) + (x − kλ)Bk,n−1(x|λ) = (1+ λ(1 − n))Bk,n−1(x|λ). (2.5) Therefore, by (2.5), we obtain the following theorem. Theorem 2.3. For k ∈ N ∪{0}, n ∈ N, with k ≤ n − 1, and x ∈ [0, 1], we have (n − k)Bk,n(x|λ) + (k + 1)Bk+1,n(x|λ)=(1+ λ(1 − n))Bk,n−1(x|λ). (2.6) From (2.1), we have n − k +1 n − (k − 1)λ Bk− ,n(x|λ) k 1 − x − (n − k)λ 1 n − k +1 n − (k − 1)λ n = (x)k− ,λ(1 − x)n−k ,λ (2.7) k 1 − x − (n − k)λ k − 1 1 +1 n! = (x)k− ,λ(1 − x)n−k,λ = Bk,n(x|λ). k!(n − k)! 1 Therefore, by (2.7), we obtain the following theorem. DEGENERATEBERNSTEINPOLYNOMIALS 5 Theorem 2.4. For n, k ∈ N, with k ≤ n, we have n − k +1 n − (k − 1)λ Bk− ,n(x|λ)= Bk,n(x|λ). k 1 − x − (n − k)λ 1 For 0 ≤ k ≤ n, we get (1 − x − (n − k − 1)λ)Bk,n−1(x|λ) + (x − (k − 1)λ)Bk−1,n−1(x|λ) n − 1 = (1 − x − (n − k − 1)λ) (x) (1 − x) − − k k,λ n 1 k,λ n − 1 + (x − (k − 1)λ) (x)k− ,λ(1 − x)n−k,λ k − 1 1 (2.8) n − 1 n − 1 = (x)k,λ(1 − x)n−k,λ + (x)k,λ(1 − x)n−k,λ k k − 1 n − 1 n − 1 n = + (x)k,λ(1 − x)n−k,λ = (x)k,λ(1 − x)n−k,λ. k k − 1 k Therefore, by (2.8), we obtain the following theorem. Theorem 2.5. ( Recurrence formula). For k,n ∈ N, with k ≤ n − 1, x ∈ [0, 1], we have (1 − x − (n − k − 1)λ)Bk,n−1(x|λ) + (x − (k − 1)λ)Bk−1,n−1(x|λ)= Bk,n(x|λ). Remark 1. For n ∈ N, we have n k n k n B (x|λ)= (x) (1 − x) − n k,n n k k,λ n k,λ k k X=0 X=0 n n− n − 1 1 n − 1 = (x)k,λ(1 − x)n−k,λ = (x)k ,λ(1 − x)n− −k,λ k − 1 k +1 1 k k X=1 X=0 n−1 n − 1 n−1 = (x − kλ) (x) (1 − x) − − = (x − kλ)(x ⊕ (1 − x)) . k k,λ n 1 k,λ λ k X=0 6 TAEKYUNKIMANDDAESANKIM Now, we observe that n k n 2 k(k − 1) n Bk,n(x|λ)= (x)k,λ(1 − x)n−k,λ n n(n − 1) k k=2 2 k=2 X Xn k(k − 1) n = (x)k,λ(1 − x)n−k,λ n(n − 1) k k=2 Xn n − 2 = (x)k,λ(1 − x)n−k,λ k − 2 k X=2 n−2 n − 2 = (x) (1 − x) − − k k+2,λ n 2 k,λ k X=0 n−2 n − 2 = (x − kλ)(x − (k + 1)λ) (x) (1 − x) − − .

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