Preconditioning Filter Bank Decomposition Using Structured Normalized Tight Frames by Martin Ehler

“…We start with a given generalized frame whose elements allow for fast matrix vector multiplication, as, for instance, convolution operators, and compute a normalized tight frame, for which signal analysis and synthesis still preserve those fast algorithmic schemes.…”
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Traveling Waves for Delayed Cellular Neural Networks with Nonmonotonic Output Functions by Zhi-Xian Yu, Rong Yuan, Cheng-Hsiung Hsu, Ming-Shu Peng

“…This work investigates traveling waves for a class of delayed cellular neural networks with nonmonotonic output functions on the one-dimensional integer lattice Z. …”
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Neural network inspired efficient scalable task scheduling for cloud infrastructure by Punit Gupta, Arnaav Anand, Pratyush Agarwal, Gavin McArdle

“…In this work, we aim to use the Harmony Search Algorithm and neural networks to create a fault aware system for optimal usage of cloud resources. …”
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Forecast and Evaluation of Educational Economic Contribution Based on Fuzzy Neural Network by RuiFeng Liu, Min Wu

“…According to the theory that the degree of education of workers in educational economics has a certain positive relationship with social labor productivity, the fuzzy system and neural network modeling mechanism are used to establish the fuzziness of laborers’ education level to social productivity (per capita national income). …”
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Application of Neural Network and Virtual Reality Technology in Digital Video Effects by Liao Jiang

“…Applying the neural network and virtual reality technology can improve the quality and efficiency of digital video special effects production.…”
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Reading and Calculation Neural Systems and Their Weighted Adaptive Use for Programming Skills by Joao Castelhano, Isabel C. Duarte, Joao Duraes, Henrique Madeira, Miguel Castelo-Branco

“…Neural Plasticity…”
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Dual-Targeted adversarial example in evasion attack on graph neural networks by Hyun Kwon, Dae-Jin Kim

Subjects: “…Graph neural network…”
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DWNet: Dual-Window Deep Neural Network for Time Series Prediction by Jin Fan, Yipan Huang, Ke Zhang, Sen Wang, Jinhua Chen, Baiping Chen

“…In this paper, we propose a dual-window deep neural network (DWNet) to predict time series. The dual-window mechanism allows the model to mine multigranularity dependencies of time series, such as local information obtained from a short sequence and global information obtained from a long sequence. …”
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Producing secure multimodal biometric descriptors using artificial neural networks by Dogu Cagdas Atilla, Raghad Saeed Hasan Alzuhairi, Cagatay Aydin

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Neural progenitor cell-derived exosomes in ischemia/reperfusion injury in cardiomyoblasts by Oiva Arvola, Virpi Stigzelius, Minna Ampuja, Riikka Kivelä

Subjects: “…Neural stem cells…”
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Bacterial, fungal and parasitic co-infections in leprosy: A scoping review. by Luis Alberto Ribeiro Fróes, Tereza Setsuko Toma, Marie Jachiet, Laurie Rousset, Rosana Evangelista Poderoso, Maria Angela Bianconcini Trindade

“…Unlike prior studies reporting increased leprosy reactions in chronic viral co-infections, our findings did not indicate any increase among bacterial, fungal, or parasitic co-infections. Rather, co-infections with tuberculosis and leishmaniasis appeared to reduce leprosy reactions.…”
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Computer-aided cholelithiasis diagnosis using explainable convolutional neural network by Dheeraj Kumar, Mayuri A. Mehta, Ketan Kotecha, Ambarish Kulkarni

Subjects: “…Explainable convolutional neural network…”
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Real-Time Optimal Approach and Capture of ENVISAT Based on Neural Networks by Hongjue Li, Yunfeng Dong, Peiyun Li

“…A neural network-based controller is developed to enable a chaser spacecraft to approach and capture a disabled Environmental Satellite (ENVISAT). …”
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A Singleton Infant with Bilateral Renal Agenesis and Normal Pulmonary Function by Lovya George, Winston Manimtim, Jotishna Sharma

“…There have been rare case reports of normal pulmonary function in the presence of bilateral renal agenesis in monoamniotic discordant twins, but this has never been reported in a singleton pregnancy. …”
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Proximal Neural Networks based reconstruction for few-view CT applications by Hoang Trieu Vy Le, Caroline Bossuyt, Julie Escoda, Marius Costin, Jan De Beenhouwer, Jan Sijbers

“…Additionally, they feature much simpler architectures compared to traditional neural networks. …”
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Identification of Weakly Pitch-Shifted Voice Based on Convolutional Neural Network by Yongchao Ye, Lingjie Lao, Diqun Yan, Rangding Wang

“…In this paper, we proposed a convolutional neural network (CNN) to detect not only strongly pitch-shifted voice but also weakly pitch-shifted voice of which the shifting factor is less than ±4 semitones. …”
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General Recurrent Neural Network for Solving Generalized Linear Matrix Equation by Zhan Li, Hong Cheng, Hongliang Guo

“…If the linear activation function is utilized, the neural state matrix of the nonlinear recurrent neural network can globally and exponentially converge to the unique theoretical solution of GLME. …”
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Algorithm of Strawberry Disease Recognition Based on Deep Convolutional Neural Network by Li Ma, Xueliang Guo, Shuke Zhao, Doudou Yin, Yiyi Fu, Peiqi Duan, Bingbing Wang, Li Zhang

“…In this paper, based on the deep convolution neural network technology, the recognition of strawberry common diseases was studied, as well as a new method based on deep convolution neural network (DCNN) strawberry disease recognition algorithm, through the normal training of strawberry image feature representation in different scenes, and then through the application of transfer learning method, the strawberry disease image features are added to the training set, and finally the features are classified and recognized to achieve the goal of disease recognition. …”
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Bayesian Inference of Ammunition Consumption Based on Normal-Inverse Gamma Distribution by Haobang Liu, Xianming Shi, Xiaojuan Chen, Yuan Li, Mei Zhao, Yongchao Jiang

“…To address the problems of high cost of new ammunition experiment, few data of field test and low accuracy of consumption prediction, this article proposes a Bayesian estimation method of ammunition consumption based on normal-inverse gamma distribution, and estimates the hyperparameters in the prior distribution through the prior information from the consumption of ammunition under different damage degrees of point targets, based on the normal distribution phenomenon of ammunition consumption at each damage degree. …”
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Individual Differences in Placebo Analgesia: Functional Connectivity and Neural Mechanisms [Letter] by Cao H, Zhang Y, Bai L, Ma X

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