We propose a method for handwritten Arabic word recognition based on the combination of the Ridgelet transform and SVMs. Ridgelets are used for generating pertinent features of handwritten words while the classificati...
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In this paper, a novel unified channel model framework is proposed for cooperative multiple-input multiple-output (MIMO) wireless channels. The proposed model framework is generic and adaptable to multiple cooperative...
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In this paper, a novel unified channel model framework is proposed for cooperative multiple-input multiple-output (MIMO) wireless channels. The proposed model framework is generic and adaptable to multiple cooperative MIMO scenarios by simply adjusting key model parameters. Based on the proposed model framework and using a typical cooperative MIMO communication environment as an example, we derive a novel geometry-based stochastic model (GBSM) applicable to multiple wireless propagation scenarios. The proposed GBSM is the first cooperative MIMO channel model that has the ability to investigate the impact of the local scattering density (LSD) on channel characteristics. From the derived GBSM, the corresponding multi-link spatial correlation functions are derived and numerically analyzed in detail.
In this paper an FPGA-based implementation of Chaotic Pulse Position Modulation (CPPM) is described. The model of transmission in noisy channel is demonstrated. The result shows the operation, performance and feasibil...
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This work provides a novel framework for identifying coma and brain death consciousness states by analysing frequency power and phase synchrony features from electroencephalogram (EEG). The proposed analysis of pairs ...
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ISBN:
(纸本)9781424441198
This work provides a novel framework for identifying coma and brain death consciousness states by analysing frequency power and phase synchrony features from electroencephalogram (EEG). The proposed analysis of pairs of EEG electrodes using complex extensions of Empirical Mode Decomposition (EMD) permits the extraction of information related to the state of the brain function. Analysis on 34 subjects in the coma and quasi-brain-death states suggests that phase synchrony constitutes a feasible feature to discriminate quasibrain- death from coma state. Thus, illustrate the effectiveness of the proposed methods for brain consciousness identification. The predictive power of the features extracted is evaluated by building classification models using support vector machine (SVM) and evaluation the models through receiver operating characteristic (ROC) analysis.
Diffusion kurtosis imaging (DKI), an extension of diffusion tensor imaging (DTI), provides a practical method to describe non-Gaussian water diffusion in neural tissues. The sensitivity of DKI to detect the subtle cha...
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ISBN:
(纸本)9781424441198
Diffusion kurtosis imaging (DKI), an extension of diffusion tensor imaging (DTI), provides a practical method to describe non-Gaussian water diffusion in neural tissues. The sensitivity of DKI to detect the subtle changes in several chosen brain structures has been studied. However, intuitive and holistic methods to validate the merits of DKI remain to be explored. In this paper, tract-based spatial statistics (TBSS) was used to demonstrate white matter alterations in both DKI and DTI parameters in preschool children (1-6 years;n=10). Correlation analysis was also performed in multiple regions of interest (ROIs). Fractional anisotropy, mean kurtosis, axial kurtosis and radial kurtosis increased with age, while mean diffusivity and radial diffusivity decreased significantly with age. Fractional anisotropy of kurtosis and axial diffusivity were found to be less sensitive to the changes with age. These preliminary findings indicated that TBSS could be used to detect subtle changes of DKI parameters on the white matter tract. Kurtosis parameters, except fractional anisotropy of kurtosis, demonstrated higher sensitivity than DTI parameters. TBSS may be a convenient method to yield higher sensitivity of DKI.
Diffusion tensor imaging (DTI) has been widely used for nondestructive characterization of microstructures of myocardium or brain connectivity. It requires repeated acquisition with different diffusion gradients. The ...
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Diffusion tensor imaging (DTI) has been widely used for nondestructive characterization of microstructures of myocardium or brain connectivity. It requires repeated acquisition with different diffusion gradients. The long acquisition time greatly limits the clinical application of DTI. In this paper, a novel method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images in direct estimation of the diffusion tensor from highly undersampled k-space data. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.
Recently, Gutiérrez-Naranjo and Leporati considered performing basic arithmetic operations on a new class of bioinspired computing devices - spiking neural P systems (for short, SN P systems). However, the binary...
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A network code assisted HARQ system considering uplink (UL) transmission with multiple mobile stations (MSs) cooperating with a relay-station (RS) is proposed. The RS is assumed to successfully monitor and decode the ...
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