Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models by Wenshuo Yue, Kai Wu, Zhiyuan Li, Juchen Zhou, Zeyu Wang, Teng Zhang, Yuxiang Yang, Lintao Ye, Yongqin Wu, Weihai Bu, Shaozhi Wang, Xiaodong He, Xiaobing Yan, Yaoyu Tao, Bonan Yan, Ru Huang, Yuchao Yang

“…Abstract Compute-in-memory based on resistive random-access memory has emerged as a promising technology for accelerating neural networks on edge devices. It can reduce frequent data transfers and improve energy efficiency. …”
Get full text

An RBFNN-Based Direct Inverse Controller for PMSM with Disturbances by Shengquan Li, Juan Li, Yanqiu Shi

“…Considering the system uncertainties, such as parameter changes, modeling error, and external uncertainties, a radial basis function neural network (RBFNN) controller using the direct inverse method with the satisfactory stability for improving universal function approximation ability, convergence, and disturbance attenuation capability is advanced in this paper. …”
Get full text

Physics-guided actor-critic reinforcement learning for swimming in turbulence by Christopher Koh, Laurent Pagnier, Michael Chertkov

“…Our scheme, coined the actor-physicist, is an adaptation of the actor-critic algorithm in which the neural network parameterized critic is replaced with an analytically derived physical heuristic function, the physicist. …”
Get full text

EMG- BASED HAND GESTURE RECOGNITION USING DEEP LEARNING AND SIGNAL-TO-IMAGE CONVERSION TOOLS by SABRINA AKTER, BIMAL KUMAR PRAMANIK, MD EKRAMUL HAMID

“…A very deep convolutional neural network (CNN) is proposed as the gesture classifier. …”
Get full text

A Hybrid Model of Extreme Learning Machine Based on Bat and Cuckoo Search Algorithm for Regression and Multiclass Classification by Qinwei Fan, Tongke Fan

“…Extreme learning machine (ELM), as a new simple feedforward neural network learning algorithm, has been extensively used in practical applications because of its good generalization performance and fast learning speed. …”
Get full text

Multivariate Nonlinear Analysis and Prediction of Shanghai Stock Market by Junhai Ma, Lixia Liu

“…The results indicate that multivariate nonlinear prediction model outperforms univariate nonlinear prediction model, local linear prediction method of multivariate time series outperforms local polynomial prediction method, and BP neural network method. Multivariate nonlinear prediction model is a useful tool for stock price prediction in emerging markets.…”
Get full text

A Dynamic Prediction Model of Financial Distress in the Financial Sharing Environment by Jie Zhu, Hong Zhu, Nan Lin

“…Then, based on the probabilistic neural network (PNN), this study constructed a dynamic prediction model of financial distress and used experimental results to verify the effectiveness and feasibility of the constructed model.…”
Get full text

Cross-Linguistic Similarity Evaluation Techniques Based on Deep Learning by Jun Li, Jing Zhang, Mengjie Qian

“…For the cross-linguistic similarity problem, a twin network model with ordered neuron long- and short-term memory neural network as a subnet is proposed. The model fuses bilingual word embeddings and encodes the representation of input sequences by ordered neuron long- and short-term memory neural networks. …”
Get full text

Pedestrian Detection Algorithm Combining Attention Mechanism and Nonmaximum Suppression Method by Duo Pan, Xuemei Zhou

“…Experimental results show that the detection accuracy of the proposed algorithm is significantly higher than that of the traditional convolutional neural network algorithm.…”
Get full text

An Efficient Algorithm for Ill-Conditioned Separable Nonlinear Least Squares by Jiayan Wang, Lanlan Guo, Zongmin Li, Xueqin Wang, Zhengqing Fu

“…Numerical experiments are performed using RBF neural network data, and the experimental results are analyzed in terms of both qualitative and quantitative indicators. …”
Get full text

Robust Trajectory Tracking of Uncertain Systems via Adaptive Critic Learning by Ziliang Zhao, Qinglin Zhu, Bin Guo

“…To realize the optimal control, the derived Hamilton–Jacobi–Bellman equation (HJBE) is solved by training a critic neural network (CNN). Finally, two innovative critic learning techniques are suggested to calculate the unknown NN weights, where the convergence of NN weights can be guaranteed. …”
Get full text

Improved Deep Learning Method for Intelligent Analysis of Sports Training Posture by Xianyou Yan

“…Thus, the stronger driving force of joint weights in the neural network is improved, the low importance of joint attention is reduced, and the high importance of joint attention is enhanced. …”
Get full text

Communication, latéralité et cerveau chez les primates humains et non humains : vers une origine gestuelle ou multimodale du langage ? by Adrien Meguerditchian, Hélène Cochet, Catherine Wallez, Jacques Vauclair

“…Most language functions are under the dominance of the left cerebral hemisphere and involve a complex neural network in which some cerebral regions play a key-role such as Broca’s and Wernicke's areas within the frontal and the temporal lobes respectively. …”
Get full text

Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems by Muhammad Akram, Ather Ashraf, Mansoor Sarwar

“…In this paper, the intuitionistic fuzzy organizational and neural network models, intuitionistic fuzzy neurons in medical diagnosis, intuitionistic fuzzy digraphs in vulnerability assessment of gas pipeline networks, and intuitionistic fuzzy digraphs in travel time are presented as examples of intuitionistic fuzzy digraphs in decision support system. …”
Get full text

Research on Pneumothorax Classification Model of DenseNet Based on Multilayer Network Optimization by Hongliang Huang, Qike Wang, Lidong Wang

“…This method optimizes multiple network layers and ensures the convergence of the neural network by reducing the learning rate with each iteration. …”
Get full text

Global Asymptotic Almost Periodic Synchronization of Clifford-Valued CNNs with Discrete Delays by Yongkun Li, Jianglian Xiang

“…In this paper, we are concerned with Clifford-valued cellular neural networks (CNNs) with discrete delays. Since Clifford algebra is a unital associative algebra and its multiplication is noncommutative, to overcome the difficulty of the noncommutativity of the multiplication of Clifford numbers, we first decompose the considered Clifford-valued neural network into 2m2n real-valued systems. …”
Get full text

Physics Informed by Deep Learning: Numerical Solutions of Modified Korteweg-de Vries Equation by Yuexing Bai, Temuer Chaolu, Sudao Bilige

“…In this paper, with the aid of symbolic computation system Python and based on the deep neural network (DNN), automatic differentiation (AD), and limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization algorithms, we discussed the modified Korteweg-de Vries (mkdv) equation to obtain numerical solutions. …”
Get full text

A Motion Image Pose Contour Extraction Method Based on B-Spline Wavelet by null Chen chen, Daohui Bi

“…Moving images are acquired through the visual system, the information fusion process is used to perform statistical analysis on the images containing motion information, the location of the motion area is determined, convolutional neural network technology is used to preprocess the initial motion image pose contour, and B-spline wavelet theory is used. …”
Get full text

Comparative study on deep and machine learning approaches for predicting wind pressures on tall buildings by Mosbeh R. Kaloop, Abidhan Bardhan, Pijush Samui, Jong Wan Hu, Mohamed Elsharawy

“…Two deep learning methods viz deep belief network (DBN) and deep neural network (DNN), and five machine learning methods namely feedforward neural network, extreme learning machine, weighted extreme learning machine, random forest, and gradient boosting machine were evaluated, and compared in predicting the design wind pressures on tall buildings. …”
Get full text

Drug Efficacy Recommendation System of Glioblastoma (GBM) Using Deep Learning by Sajid Naveed, Mujtaba Husnain, Ali Samad, Amna Ikram, Hina Afreen, Ghulam Gilanie, Najah Alsubaie

“…A panel of 47 genes associated with GBM was processed using two deep learning models: Artificial Neural Network (ANN) and Convolutional Neural Network (CNN). …”
Get full text