Background: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose...
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Background: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize either the l(2) norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise. Results: We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l(2) norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm. Conclusions: Extensive experiments on six cancer benchmark sets demonstrate that the
We investigate Gaussian widely linear preceding known as improper Gaussian signaling for the cellular uplink with inter-cell interference, known as interference multiple access channel (IMAC). This transmission scheme...
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ISBN:
(纸本)9781538660096
We investigate Gaussian widely linear preceding known as improper Gaussian signaling for the cellular uplink with inter-cell interference, known as interference multiple access channel (IMAC). This transmission scheme provides extra degrees of freedom by treating the real and imaginary components of the complex Gaussian signal differently. Since current standards mainly utilize linear beamforming for waveform generation, we highlight the benefits of widely linear beamforming over multiple temporal dimensions (symbol extension in time) in the IMAC. This scheme achieves significantly higher information rates compared to conventional proper Gaussian signaling at the expense of extra complexity at the transmission phase. We study the sum-power minimization problem under rate constraints. This problem is a difference of concave functions (DC) program, hence, a non-convex problem. By numerical simulations, we observe the benefits of improper Gaussian signaling alongside symbol extension in power consumption for both single-antenna and multi-antenna base stations. Interestingly, we observe that at strong interference scenarios, the efficiency of improper Gaussian signaling outperforms conventional proper Gaussian signaling at low rate demands. Moreover, in such scenarios the sum-power required for achieving particular rate demands is significantly reduced.
We investigate Gaussian widely linear precoding known as improper Gaussian signaling for the cellular uplink with inter-cell interference, known as interference multiple access channel (IMAC). This transmission scheme...
详细信息
We investigate Gaussian widely linear precoding known as improper Gaussian signaling for the cellular uplink with inter-cell interference, known as interference multiple access channel (IMAC). This transmission scheme provides extra degrees of freedom by treating the real and imaginary components of the complex Gaussian signal differently. Since current standards mainly utilize linear beamforming for waveform generation, we highlight the benefits of widely linear beamforming over multiple temporal dimensions (symbol extension in time) in the IMAC. This scheme achieves significantly higher information rates compared to conventional proper Gaussian signaling at the expense of extra complexity at the transmission phase. We study the sum-power minimization problem under rate constraints. This problem is a difference of concave functions (DC) program, hence, a non-convex problem. By numerical simulations, we observe the benefits of improper Gaussian signaling alongside symbol extension in power consumption for both single-antenna and multi-antenna base stations. Interestingly, we observe that at strong interference scenarios, the efficiency of improper Gaussian signaling outperforms conventional proper Gaussian signaling at low rate demands. Moreover, in such scenarios the sum-power required for achieving particular rate demands is significantly reduced.
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