Mittag-Leffler Stability and Attractiveness of Pseudo Almost Periodic Solutions for Delayed Cellular Neural Networks by Zahra Eidinejad, Reza Saadati, Dušan D. Repovš

“…We consider a class of nonautonomous cellular neural networks (CNNs) with mixed delays, to study the solutions of these systems which are type pseudo almost periodicity. …”
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Identifying the Effective Factors on Neuropathic Diseases in Patients with Chronic pain Using Deep Neural Networks by Mobin Shaterian, Mohammad Teshnehlab

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Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features by Emmanuel Adetiba, Oludayo O. Olugbara

“…This paper reports an experimental comparison of artificial neural network (ANN) and support vector machine (SVM) ensembles and their “nonensemble” variants for lung cancer prediction. …”
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Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Device by salam waley shneen, Rajaa khalaf Gaber, Rasha Saad Salih, Suaad Makki Jiaad

“…The current work was developed under the title of Artificial Neural Network (ANN) Proportional Integral Derivative (PID) for the arm rehabilitation device and included building and designing the simulation model and simulation results for the arm rehabilitation device. …”
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Existence and Global Exponential Stability of Periodic Solutions for General Neural Networks with Time-Varying Delays by Xinsong Yang

“…By using the coincidence degree theorem and differential inequality techniques, sufficient conditions are obtained for the existence and global exponential stability of periodic solutions for general neural networks with time-varying (including bounded and unbounded) delays. …”
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Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays by Kaibo Shi, Hong Zhu, Shouming Zhong, Yong Zeng, Yuping Zhang, Li Liang

“…This paper investigates the problem of dependent stability criteria for neutral type neural networks with mixed time-varying delays. Firstly, some new delay-dependent stability results are obtained by employing the more general partitioning approach and generalizing the famous Jensen inequality. …”
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Adversarial measurements for convolutional neural network-based energy theft detection model in smart grid by Santosh Nirmal, Pramod Patil, Sagar Shinde

“…Electricity or Energy theft detection (ETD) systems utilizing machine learning, particularly those employing neural networks, have high accuracy and have become popular in literature, achieving higher detection performance. …”
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Sandy Soil Liquefaction Prediction Based on Clustering-Binary Tree Neural Network Algorithm Model by Yu Wang, Jiachen Wang

“…The neural network algorithm is a small sample machine learning method built on the statistical learning theory and the lowest structural risk principle. …”
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Short-term power consumption forecasting using neural networks with first- and second-order differencing by Meftah Elsaraiti

“…Recent advancements in machine learning, particularly long short-term memory (LSTM) networks, have addressed some of these limitations by leveraging neural network architectures capable of learning complex temporal dependencies. …”
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IM- LTS: An Integrated Model for Lung Tumor Segmentation using Neural Networks and IoMT by Jayapradha J, Su-Cheng Haw, Naveen Palanichamy, Kok-Why Ng, Senthil Kumar Thillaigovindhan

“…With that concern, this work aims to develop an Integrated Model (IM- LTS) for Lung Tumor Segmentation using Neural Networks (NN) and the Internet of Medical Things (IoMT). …”
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Retracted: Parallel Bookkeeping Path of Accounting in Government Accounting System Based on Deep Neural Network by Journal of Electrical and Computer Engineering

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Neural Network Based Vibration Analysis with Novelty in Data Detection for a Large Steam Turbine by K. P. Kumar, K.V.N.S. Rao, K.R. Krishna, B. Theja

“…The Mat lab 7 codes are applied to generate program using neural networks toolbox.…”
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Greenhouse environmental monitoring and control system based on improved fuzzy PID and neural network algorithms by Guan Hongqiang

Subjects: “…backpropagation neural network…”
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A Next-Generation Codebook Evolution Strategy for Massive Arrays Using Deep Neurals Networks by Minwoo Choi, Wonjin Sung

“…The process is operated in an iterative fashion to produce updated versions of the codebook with the reduced return of the loss function at the deep neural network (DNN). The time-varying codebook for each BS automatically reflects the characteristics of a given wireless environment to adapt to its channel and traffic conditions. …”
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Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays by Xiaofeng Chen, Qiankun Song, Yurong Liu, Zhenjiang Zhao

“…The impulsive complex-valued neural networks with three kinds of time delays including leakage delay, discrete delay, and distributed delay are considered. …”
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Neural Network Based Adaptive Backstepping Control for Electro-Hydraulic Servo System Position Tracking by Zhenshuai Wan, Longwang Yue, Yu Fu

“…To cope with this issue, an adaptive backstepping controller based on neural network (NN) is proposed in this paper. A radial-basis-function neural network (RBF NN) is constructed to approximate the lumped uncertainties caused by modeling uncertainties and external disturbances, where the adaptive law is adopted to adjust controller parameters online. …”
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Ensembles of spectral-spatial convolutional neural network models for classifying soil types in hyperspectral images by N.A. Firsov, V.V. Podlipnov, N.A. Ivliev, D.D. Ryskova, A.V. Pirogov, A.A. Muzyka, A.R. Makarov, V.E. Lobanov, V.I. Platonov, A.N. Babichev, V.A. Monastyrskiy, V.I. Olgarenko, D.P. Nikolaev, R.V. Skidanov, A.V. Nikonorov, N.L. Kazanskiy, V.A. Soyfer

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Mean Square Exponential Stability of Stochastic Cohen-Grossberg Neural Networks with Unbounded Distributed Delays by Chuangxia Huang, Lehua Huang, Yigang He

“…This paper addresses the issue of mean square exponential stability of stochastic Cohen-Grossberg neural networks (SCGNN), whose state variables are described by stochastic nonlinear integrodifferential equations. …”
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Testing convolutional neural network based deep learning systems: a statistical metamorphic approach by Faqeer ur Rehman, Clemente Izurieta

Subjects: “…Testing convolutional neural networks (CNNs)…”
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Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy by Jin-E Zhang, Huan Liu

“…This paper proposes the event-triggered strategy (ETS) for multiple neural networks (NNs) with parameter uncertainty and time delay. …”
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