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52 The Gaussian case As always, the Gaussian case is the best understood The structure of stochastic, Gaussian, self-similar processes, also possessing stationary increments, is well-known In his article [DOB 79], Dobrushin presents contemporary results, including his own works, in a de nitive style and in the framework of generalized stochastic processes Here, we give a stochastic processes version 521 Self-similar Gaussian processes with r-stationary increments To describe Dobrushin s results, we need some notations 5211 Notations 1, be the usual Euclidean space; with x = (x1 , , xd ), and Let Rd , d d 2 d 2 |x| = 1 xk Let xy = 1 xk yk denote the scalar product of vectors x and y Let k = (k1 , , kd ) Nd be a multi-index of length |k| = k1 + + kd We de ne Dk = ( x1 )k1 ( xd )kd Let f be a function of Rd in R Let TF (f ) denote its Fourier transform and TF 1 (f ) its inverse Fourier transform When f is a distribution, the same notations are used for the (inverse) Fourier transform Let us ecall that, for k N: TF (Dk f )( ) = i|k| k TF (f )( ) Let us denote by S(Rd ) (or S where there is no ambiguity) the Schwartz space of functions C with rapid decrease and rapid decrease derivatives; S (Rd ) (or S ) then denotes the space of moderate distributions Let T S The translation operator k def is de ned as k T, = T, k for S, with k (x) = (x + k) Let f be a function of Rd in R and n an integer Let f n denote a function on def (Rd )n de ned as f n (x1 , , xn ) = (f (x1 ), , f (xn )) Finally, for k Rd , let us introduce the translation operator k f n = ( k f (x1 ), , k f (xn )) 5212 De nitions In this section, the same notations are used for distributions and functions DEFINITION 52 Let (X(x)), with x Rd , be a (possibly) generalized stochastic process: X is said to be stationary if, for any integer n and any h Rd : h X n = X n.

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working, and what plans are already established to address or change these components This is much more technical, but it is still worthwhile to collect There are many different ways that reporting systems can be created Even for a data warehouse there are many components involved You need to understand what technology is being used to extract, prepare, publish, and use the data 9 provides more details about each of these components when they are part of a data warehouse For now, ask the following questions to help identify the technology and tools currently being used: What technologies or products are used Are these are the most current release of the product Is this component stable Does this component perform acceptably Is this component supportable Is this component sustainable for the future Are there any plans in place that will modify this technical environment Table 3-2 shows an example of how to track this technology inventory By documenting a summary of technical details, you can keep track of all the different moving parts of the system You may ask what technology each system uses for the technical components listed in Table 3-2 More information about what each of these different technologies and tools does is rovided in 9 In addition to the Technology Inventory Matrix, it is helpful to document the answers to the other questions One group may be using the most current release of a tool, which is meeting their needs Another group may use an earlier version of the same product but without the same level of satisfaction The Technology Inventory Matrix provides a handy cross-reference for nding the appropriate detail for a single tool You need to look at the details for each group that is using that tool.

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