Results 21 to 30 of about 349,230 (288)

Comparison of Neural Network and Recurrent Neural Network to Predict Rice Productivity in East Java

JITeCS (Journal of Information Technology and Computer Science), 2021
Rice is the staple food for most of the population in Indonesia which is processed from rice plants. To meet the needs and food security in Indonesia, a prediction is required.
Andi Hamdianah, Wayan Firdaus Mahmudy, Eko Widaryanto   +2 more
doaj   +1 more source

Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control [PDF]

, 2012
It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for ...
A Banerjee, A Litwin-Kumar, C Miall, C van Vreeswijk, CA Skarda, CV Buhusi, D Bueti, D Durstewitz, D Durstewitz, D Sussillo, DA Crowe, Dean V Buonomano, DJ Watts, DV Buonomano, DV Buonomano, DV Buonomano, DV Buonomano, DV Buonomano, E Pastalkova, EM Izhikevich, G Boffetta, G Fagiolo, H Jaeger, H Jaeger, H Kantz, H Merchant, H Sompolinsky, J Coull, JF Medina, JF Medina, JJ Hopfield, JK Liu, JX Li, K Rajan, M London, M Monteforte, M Rabinovich, MA Long, MB Ahrens, MD Mauk, MM Churchland, MS Goldman, MS Matell, N Brunel, P Janssen, P Simen, RB Ivry, RB Ivry, RHR Hahnloser, RM Church, Rodrigo Laje, S Ganguli, S Song, XJ Wang   +53 more
core   +2 more sources

Recurrent neural network wave functions

Physical Review Research, 2020
A core technology that has emerged from the artificial intelligence revolution is the recurrent neural network (RNN). Its unique sequence-based architecture provides a tractable likelihood estimate with stable training paradigms, a combination that has ...
Mohamed Hibat-Allah, Martin Ganahl, Lauren E. Hayward, Roger G. Melko, Juan Carrasquilla   +4 more
doaj   +1 more source

Clustering Based on Continuous Hopfield Network

Mathematics, 2022
Clustering aims to group n data samples into k clusters. In this paper, we reformulate the clustering problem into an integer optimization problem and propose a recurrent neural network with n×k neurons to solve it. We prove the stability and convergence
Yao Xiao, Yashu Zhang, Xiangguang Dai, Dongfang Yan   +3 more
doaj   +1 more source

General Recurrent Neural Network for Solving Generalized Linear Matrix Equation

Complexity, 2017
This brief proposes a general framework of the nonlinear recurrent neural network for solving online the generalized linear matrix equation (GLME) with global convergence property. If the linear activation function is utilized, the neural state matrix of
Zhan Li, Hong Cheng, Hongliang Guo
doaj   +1 more source

A Scheme with Acoustic Emission Hit Removal for the Remaining Useful Life Prediction of Concrete Structures

Sensors, 2021
In this study, a scheme of remaining useful lifetime (RUL) prognosis from raw acoustic emission (AE) data is presented to predict the concrete structure’s failure before its occurrence, thus possibly prolong its service life and minimizing the risk of ...
Tuan-Khai Nguyen, Zahoor Ahmad, Jong-Myon Kim   +2 more
doaj   +1 more source

Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)

IEEE Access, 2022
The paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator.
Bartosz Puchalski
doaj   +1 more source

A new approach to seasonal energy consumption forecasting using temporal convolutional networks

Results in Engineering, 2023
There has been a significant increase in the attention paid to resource management in smart grids, and several energy forecasting models have been published in the literature.
Abdul Khalique Shaikh, Amril Nazir, Nadia Khalique, Abdul Salam Shah, Naresh Adhikari   +4 more
doaj   +1 more source

Detection of Shoplifting on Video Using a Hybrid Network

Computation, 2022
Shoplifting is a major problem for shop owners and many other parties, including the police. Video surveillance generates huge amounts of information that staff cannot process in real time.
Lyudmyla Kirichenko, Tamara Radivilova, Bohdan Sydorenko, Sergiy Yakovlev   +3 more
doaj   +1 more source

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks [PDF]

Biological Cybernetics, 2012
Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in ...
Bitzer, S., Kiebel, S.
openaire   +4 more sources