The stability behaviour of the iterative decoding (ID) of Turbo-Codes and its innuence on the overall performance are discussed. Several criteria to characterize the ID are proposed and the most reliable ones are determined. These criteria are used to partition the transnitted blocks into stable and unstable ones. For unstable blocks the decoding step is determined which most likely produces a ...

Sediment transport constantly influences river and civil structures and the lack ofinformation about its exact amount makes management efforts less effective. Hence,achieving a proper procedure to estimate the sediment load in rivers is important. We usedsupport vector machine model to estimate the sediments of the Kakareza River in LorestanProvince and the results were compared with those obta...

The main statistics used in rough set data analysis, the approximation quality, is of limited value when there is a choice of competing models for predicting a decision variable. In keeping within the rough set philosophy of non–invasive data analysis, we present three model selection criteria, using information theoretic entropy in the spirit of the minimum description length principle. Our ma...

This paper examines orthonormal regression and wavelet denoising within the Minimum Message Length (MML) framework. A criterion for hard thresholding that naturally incorporates parameter shrinkage is derived from a hierarchical Bayes approach. Both parameters and hyperparameters are jointly estimated from the data directly by minimisation of a two-part message length, and the threshold implied...

The error-entropy-minimization approach in adaptive system training is addressed in this paper. The effect of Parzen windowing on the location of the global minimum of entropy has been investigated. An analytical proof that shows the global minimum of the entropy is a local minimum, possibly the global minimum, of the nonparametrically estimated entropy using Parzen windowing with Gaussian kern...

this paper presents a new multi-sensor data fusion method based on the combination of wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for...