and Applied Analysis 3 2. Preliminaries In this section, we complete notations and recall some known definitions. Let K X be the class of all nonempty and compact subset of X. If A ∈ K X we define the ε-neighbourhood of A as the set N A, ε {x ∈ X | d x,A < ε}, 2.1 where d x,A infa∈A‖x − a‖. The Hausdorff separation ρ A,B of A,B ∈ K X is defined by ρ A,B inf{ε > 0 | A ⊆ N B, ε }. 2.2 The Hausdor...

Let {Rt, 0 ≤ t ≤ 1} be a symmetric α-stable Riemann-Liouville process with Hurst parameterH > 0. Consider a translation invariant, β-self-similar, and p-pseudo-additive functional semi-norm ||.||. We show that if H > β+1/p and γ = (H − β− 1/p), then lim ε↓0 ε logP [||R|| ≤ ε] = −K ∈ [−∞, 0), with K finite in the Gaussian case α = 2. If α < 2, we prove that K is finite when R is continuous and H...

In this paper we investigate linear error correcting codes and projective caps related to the Grassmann embedding ε k of an orthogonal Grassmannian ∆k. In particular, we determine some of the parameters of the codes arising from the projective system determined by ε k (∆k). We also study special sets of points of ∆k which are met by any line of ∆k in at most 2 points and we show that their imag...

A double sequence x = {xk,l} of points in R is slowly oscillating if for any given ε > 0, there exist α = α(ε) > 0, δ = δ(ε) > 0, and N = N(ε) such that |xk,l−xs,t| < ε whenever k, l ≥ N(ε) and k ≤ s ≤ (1 + α)k, l ≤ t ≤ (1 + δ)l. We study continuity type properties of factorable double functions defined on a double subset A × A of R into R, and obtain interesting results related to uniform cont...

In previous lectures we defined a randomness extractor as follow, Definition 1 Function Ext : {0, 1}n × {0, 1}d → {0, 1}m is (k, ε)extractor if for any distribution W ∈ {0, 1}n, with H∞(W ) ≥ k SD(Ext(W ; I), Um) ≤ ε. ♦ If (I,Ext(W ; I) ≈ε (I, Um) we say Ext is a strong extractor. We saw that if H = {hi : {0, 1}n → {0, 1}m|∀i ∈ {0, 1}d} is a universal hash family and m ≤ k − 2 log(1/ε) then Ext...

We describe a deterministic algorithm that, for constant k, given a k-DNF or kCNF formula φ and a parameter ε, runs in time linear in the size of φ and polynomial in 1/ε and returns an estimate of the fraction of satisfying assignments for φ up to an additive error ε. For k-DNF, a multiplicative approximation is also achievable in time polynomial in 1/ε and linear in the size of φ. Previous alg...