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This paper addresses the estimation of fuzzy Gaussian distribution mixture with applications to unsupervised statistical fuzzy image segmentation. In a general way, the fuzzy approach enriches the current statistical models by adding a fuzzy class, which has several interpretations in signal processing. One such interpretation in image segmentation is the(More)
A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms situated halfway between Markovian and neural paradigms. A new systematic way to classify these algorithms is proposed. Four specific classes of models are described. The first one is(More)
The extraction of highly discriminant features is crucial for successful species identification of fish shoals if backscattered narrowband signals do indeed contain discrimi-nant information. Four different methods of feature extraction are described and applied to the same data, providing new descriptors expected to improve species identification.(More)
In this paper we present post-integration processing in order to improve the sensitivity of electronic support measure (ESM) receivers. Correlation methods take advantage of the periodic character of radar signals. In such cases, autocorrelation and cross-correlation improve the detection of signals with high repetition frequency. Furthermore, since the(More)