in order to capability investigation on landsat-7 satellite etm+ data in separability forest type and mapping in the zagros region, a small window digital data dating july 2001 from ghalajeh forests in the kermanshah province were analyzed. ground data were provided the cluster sampling method and with 0.36 ha. no radiometric error was found then the quality investigations. orthorectification w...

The more sophisticated fuzzy clustering algorithms, like the Gustafson–Kessel algorithm [11] and the fuzzy maximum likelihood estimation (FMLE) algorithm [10] offer the possibility of inducing clusters of ellipsoidal shape and different sizes. The same holds for the EM algorithm for a mixture of Gaussians. However, these additional degrees of freedom often reduce the robustness of the algorithm...

More sophisticated fuzzy clustering algorithms, like the Gustafson–Kessel algorithm [11] and the fuzzy maximum likelihood estimation (FMLE) algorithm [10] offer the possibility of inducing clusters of ellipsoidal shape and different sizes. The same holds for the expectation maximization (EM) algorithm for a mixture of Gaussians. However, these additional degrees of freedom can reduce the robust...

SUMMARY Neural networks have received considerable attention in recent years. This development has been pursued primarily by non-statisticians. Consequently many statistical tools and concepts have not been utilized in this development and great claims for neural networks have sometimes been made without comparisons to standard statistical procedures. In this paper we utilize the input-output r...

In this thesis, a multi-source system for human identification is developed. The system uses three sources: face classifier, height classifier, and color classifier. In the process of developing this system, classifier combination and the integration of classifer outputs over sequences of data points were studied in detail. The method of classifier combination used relies on weighing classifier...

The overall performance of a multi-stage decision-tree classifier has been shown to be better than that of the conventional single-stage classifier with the same number of features because different feature subsets can be selected at different stages. But, the classification time increases due to the complexity of computation. The 1 inear binary tree classifier designed by the method proposed i...

For the operational application of multi-temporal ENVISAT ASAR APS data to rice mapping, a complex Wishart distribution based multi-temporal classifier was evaluated in this paper. The classification accuracy of this classifier was quantitatively compared with commonly used classifiers for optical remote sensing image classification including maximum likelihood classifier and minimum euclidean ...

this paper considers the generation of some interpretable fuzzy rules for assigning an amino acid sequence into the appropriate protein superfamily. since the main objective of this classifier is the interpretability of rules, we have used the distribution of amino acids in the sequences of proteins as features. these features are the occurrence probabilities of six exchange groups in the seque...

In this paper we investigate the large-sample behavior of the maximum likelihood estimate (MLE) of the unknown parameter θ for processes following the model dξt = θf(t)ξt dt+ dBt where f : R → R is a continuous function with period, say P > 0, and which is observed through continuous time interval [0, T ] as T → ∞. Here the periodic function f(·) is assumed known. We establish the consistency o...