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A novel method, called grayscale iteration threshold pulse coupled neural network (GIT-PCNN) was proposed for image segmentation, which integrates grayscale iteration threshold with PCNN. PCNN has been widely used in image segmentation. However, satisfactory results are usually obtained at the expense of time-consuming selection of PCNN parameters and the number of iteration. In this method, traditional...
In this paper, a novel method is proposed for face recognition based on pulse coupled neural network (PCNN) time signature. In this approach, a probe face is first extracted PCNN time signature as the recognition features, which a two-dimensional image is projected to a low one-dimensional feature space and then is classified based on the known samples. An extensive experimental investigation is conducted...
In this paper, a novel method is proposed to detect faces based on PCNN time signature and skin color segmentation, in which no training is needed. A test image is first divided into overlapped blocks and extracted PCNN time signature as the detection features, which a two-dimensional image is projected to a one-dimensional feature space. The test blocks are matched to a face template, which can be...
This study describes a new method for segmentation of Synthetic Aperture Radar (SAR) images, which integrates optimal threshold with pulse-coupled neural network (PCNN). Traditional image segmentation algorithms exhibit weak performance for SAR images due to the poor quality of SAR images. PCNN has been widely used in image segmentation. However, satisfactory results are usually obtained at the expense...
This paper proposes a novel channel tracking method based on radial basis function neural network (RBFNN) and particle filter (PF) in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system. First, we use the RBFNN to obtain the initial values of the MIMO channels, and then apply the PF method to track the variation of the channels. The fading channels are modeled...
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