The fading measurements have been addressed by the mean and covariance of the variable which depend on the distribution law of each

probability mass function. Based on the projection theory, the linear minimum variance optimal linear estimators, including filter, predictor, and smoother have been proposed.

This section presents the method proposed in this paper in order to detect road elements based on the

probability mass function measured at each particular location after filtering slow traffic conditions.

Suppose C is the set of all the covers, and it is an assumption that the selections of the covers and stegos from the set C can be described by the random variables c and s on C with the

probability mass functions (PMF) [P.sub.c] and [P.sub.s], respectively.

For multifractal measures, the

probability mass function in each segment, [p.sub.i],([delta]), also scales with segment size [delta] as [p.sub.], ([delta])[alpha][[delta].sup.[alpha]i], where [[alpha].sub.i] = log [[mu].sub.i]([delta])/ /logS is the Lipschitz-Holder relationship which describes the scaling property to each i-th segment.

(i) Code Construction for Case 1.Given a pair (R, [R.sub.e]), choose a joint

probability mass function [p.sub.U, A, S, X, Y, Z](u, a, s, x, y, z) such that

As [theta] grows large, (1) converges to the

probability mass function of a Poisson random variable.

The

probability mass function of number of customers in the orbit

The pair (X, P) will be used to denote the random vector X together with the

probability mass function P on the sample space [2.sup.[omega]] = [2.sup.{1, ...

The

probability mass function of Basic Server state

CL is defined in terms of the binomial

probability mass function, also called the binomial discrete density function, b(m; n,p),

The possible signal values are denoted by [lambda], and Pr(x = l) is the

probability mass function (PMF) of X.

Denoting as [THETA] the (unknown) accident proneness of this policyholder, the conditional

probability mass function of N is given by