The results obtained from applying the discussed method on the model parameter estimation are listed in Table 2, where the particle number is 30 and the priori probability density function is selected as the importance function.
Notice also that the CPF approach comes out of the utilization of another filtering technique (KF) producing a filtering probability density function used as importance function (IF) for the particle filtering.
Since the main applications considered for the irregular arrays involve speech (as in the case of surveillance in a cocktail party environment), the excitation of the arrays need to compute the performance metrics is colored noise with the same spectral distribution as the band importance function used in the speech intelligibility index (SII) [5].
We compute the importance function as the solution of the corresponding stationary adjoint problem.
We will present the important distribution adopted in Section 4. With the particles sequentially sampled from the importance function as each new observation arrives, the importance weights can be computed recursively in time as follow [16]: w ˜ k i = w ˜ k − 1 i p y k | x 0 : k i, y 0 : k − 1, h, G, Ψ π x k i | x 0 : k − 1 i, y 0 : k, h, G, Ψ, (11).
Initially limited to buildings, the newly established level of importance functioned as a waiting list for nominated Important Cultural Properties and as an extension for National Treasures.
The filter function can be thought of as assigning an importance to the photocurrent emitted at time t; this filter function assigns high importance during the steady-state phase of the measurement, and low importance at other times.
To reduce the variances, importance sampling is applied leading to an exponential 1 D-importance function.
Open image in new window Fig. 5 Use of adhesion-reduction agents within the six previous months, as a function of importance given to adhesions in daily surgical work.
The marginal likelihood is estimated using the harmonic mean of the likelihoods of the samples from the posterior distribution as presented in Newton and Raftery (1994), where the idea is to use the parameter posterior as the importance sampling function (12) p (y | X ) ≈ (1 m ∑ i = 1 m p (y | X, f (i ), θ (i ), k (i ) ) − 1 ) − 1, where f (i ), θ (i ), k (i ) ∼ p (f, θ, k | y ).
