We present a new method for the derivation of convolution identities for finite sums of products of Bernoulli numbers. Our approach is motivated by the role of these identities in quantum field theory and string theory. We first show that the Miki identity and the Faber-Pandharipande-Zagier (FPZ) identity are closely related, and give simple unified proofs which naturally yield a new Bernoulli ...

Abstract The principles of the energy variation method are commonly utilized in mechanics. Energy is a scalar variable, so these more convenient and simple to establish equilibrium equations compared vector-based approaches (i.e. using forces displacements). present article applied theorem order set for various complicated problems. Four examples applying include differential equation Euler – B...

We give a characterization of the family of all probability measures on the extended line (−∞,+∞], which may be obtained as the distribution of the maximum of some linear Bernoulli process. On a probability space (Ω,P) consider a linear process

Consider a given pattern H and a random text T of length n. We assume that symbols in the text occur independently, and various symbols have diierent probabilities of occurrence (i.e., the so called asymmetric Bernoulli model). We are concerned with the probability of exactly r occurrences of H in the text T. We derive the generating function of this probability, and show that asymptotically it...

Let L (u, a), oo < u < + oo denote the Fourier-Stieltjes transform, 00 f eluoda(x), of a distribution function u(x), oo < x < + co . Thus if 00 /3(x) is the distribution function which is 0, J, 1 according as x -1 < x ,< 1, 1 < x, then L (u,,8) = cos u ; and so, if b is a positive constant, cos (u/b) is the transform of the distribution function /3(bx) . Hence, if a is a positive constant, the ...

A The chaos hierarchy 12 A.1 Ergodicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 A.2 Mixing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 A.3 K Systems (Kolmogorov) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 A.4 B-Systems (Bernoulli) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

Since the 1930’s many authors have studied the distribution νλ of the random series Yλ = ∑±λn where the signs are chosen independently with probability (1/2, 1/2) and 0 < λ < 1. Solomyak recently proved that for almost every λ ∈ [ 1 2 , 1], the distribution νλ is absolutely continuous with respect to Lebesgue measure. In this paper we prove that νλ is even equivalent to Lebesgue measure for alm...