In this paper, a functions localized network with branch gates (FLN-bg) is studied, which consists of a basic network and a branch gate network. The branch gate network is used to determine which intermediate nodes of the basic network should be connected to the output node with a gate coefficient ranging from 0 to 1. This determination will adjust the outputs of the intermediate nodes of the b...

Cooperative relaying is one of the promising technology which is used to improve coverage and spatial diversity. A new relay strategy, the N Best-Relay Selection scheme is proposed to improve the bandwidth penalty and to increase the spatial diversity by using a sub-optimal allocation for the relay relative distance between the source and destination in a multi-hop cooperative systems. A single...

Perceptrons is a simple neural network that works as an alternative to the commonly used two-bit counters branch history table (BHT) branch predictor. Perceptrons achieves increased accuracy than traditional BHT branch predictors because they can make use of longer branch histories, given the same hardware budget. Although having very similar organization to BHT branch predictors, Perceptrons’ ...

Phasor Measurement Units (PMUs) are in growing attention in recent power systems because of their paramount abilities in state estimation. PMUs are placed in existing power systems where there are already installed conventional measurements, which can be helpful if they are considered in PMU optimal placement. In this paper, a method is proposed for optimal placement of PMUs incorporating conve...

Electroencephalogram (EEG) signals have emerged as an important tool for emotion research due to their objective reflection of real emotional states. Deep learning-based EEG classification algorithms made preliminary progress, but existing models struggle with capturing long-range dependence and integrating temporal, frequency, spatial domain features limit ability. To address these challenges,...

Dear Editor, In pansharpening task, the most existing deep-learning-based pan-sharpening methods fail to fully utilize different level features, inevitably leading spectral or spatial distortions. To address this challenge, in letter, we propose a dual-branch multi-level feature aggregation network for (DMFANet). The experimental results on WorldView-II (WV-II) and QuickBird (QB) dataset confir...

Abstract Prostate image segmentation is a precondition for the diagnosis of prostate diseases and subsequent treatment. However, blurry organ edges low contrast make accurate difficult. In order to overcome difficulties, this paper proposes an innovative Multi-branch Context Awareness Network (MBCA-Net) MRI segmentation. MBCA-Net uses 3D UNet as backbone network with encoder-decoder framework. ...

Karp and Zhang developed a general randomized parallel algorithm for solving branch and bound problems. They showed that with high probability their algorithm attained optimal speedup within a constant factor (for p ≤ n/(log n)c, where p is the number of processors, n is the “size” of the problem, and c is a constant). Ranade later simplified the analysis and obtained a better processor bound. ...