Výsledky vyhledávání - Backpropagation through time algorithms

Recurrent Neural Networks Trained With Backpropagation Through Time Algorithm to Estimate Nonlinear Load Harmonic Currents Autor Mazumdar, J., Harley, R.G.

“… This paper proposes a neural network solution to this problem. A recurrent neural network trained with the backpropagation through time training algorithm is used to find…”
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Research on Cascading Fault Location of Chemical Material Networks Based on BFS-Time-Reversal Backpropagation Algorithm Autor Wang, Zheng, Li, Huapeng, Liu, Ruijie, Hou, Jingmin, Dong, Ran, Hu, Yiyi, Jia, Xiaoping, Wang, Fang

“…)-time-reversal backpropagation algorithm to study…”
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Analisis Tingkat Akurasi Variasi Algoritma Min-Max Backpropagation sebagai Pre-Processing Data Time Series Autor Mandailina, Vera, Abdillah, Abdillah, Syaharuddin, Syaharuddin

“… This paper aims to test eight types of Min-Max backpropagation algorithms with several types of data, namely static data, seational data, monotonically fluctuating data up and down…”
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Event-based backpropagation can compute exact gradients for spiking neural networks Autor Wunderlich, Timo C., Pehle, Christian

“… was previously hindered by the existence of discrete spike events and discontinuities. For the first time, this work derives the backpropagation algorithm for a continuous…”
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Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter Autor Fu, Xingang, Li, Shuhui, Fairbank, Michael, Wunsch, Donald C., Alonso, Eduardo

“… This paper explores how to incorporate FATT into the LM algorithm. The results show that the combination of the LM and FATT algorithms trains RNNs better than the conventional backpropagation through time algorithm…”
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A parallel compact Marine Predators Algorithm applied in time series prediction of Backpropagation neural network (BNN) and engineering optimization Autor Pan, Jeng-Shyang, Zhang, Zhen, Chu, Shu-Chuan, Zhang, Si-Qi, Wu, Jimmy Ming-Tai

“…This study introduces a novel approach for integrating a compact mechanism into the Marine Predator Algorithm (MPA…”
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Backpropagation through time and the brain Autor Lillicrap, Timothy P, Santoro, Adam

“… It has long been speculated that the backpropagation-of-error algorithm (backprop) may be a model of how the brain learns…”
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The Symplectic Adjoint Method: Memory-Efficient Backpropagation of Neural-Network-Based Differential Equations Autor Matsubara, Takashi, Miyatake, Yuto, Yaguchi, Takaharu

“… The backpropagation algorithm consumes memory in proportion to the number of uses times of the network size, causing practical difficulties…”
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Noise-boosted bidirectional backpropagation and adversarial learning Autor Adigun, Olaoluwa, Kosko, Bart

“… Special injected noise can then improve the algorithm’s training time and accuracy because backpropagation has a likelihood structure…”
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An Equivalence Between Adaptive Dynamic Programming With a Critic and Backpropagation Through Time Autor Fairbank, Michael, Alonso, Eduardo, Prokhorov, Danil

“… We extend DHP into a new algorithm that we call Value-Gradient Learning, VGL(λ), and prove equivalence of an instance of the new algorithm to Backpropagation Through Time for Control with a greedy policy…”
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The backpropagation algorithm implemented on spiking neuromorphic hardware Autor Renner, Alpha, Sheldon, Forrest, Zlotnik, Anatoly, Tao, Louis, Sornborger, Andrew

“… In particular, the workhorse of modern deep learning, the backpropagation algorithm, has proven difficult to translate to neuromorphic hardware…”
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Efficient training of spiking neural networks with temporally-truncated local backpropagation through time Autor Guo, Wenzhe, Fouda, Mohammed E., Eltawil, Ahmed M., Salama, Khaled Nabil

“… The well-known backpropagation through time (BPTT) algorithm proposed to train SNNs suffers from large memory footprint and prohibits backward and update unlocking…”
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Robust Neural Control of Discrete Time Uncertain Nonlinear Systems Using Sliding Mode Backpropagation Training Algorithm Autor Zaidi, Imen, Chtourou, Mohamed, Djemel, Mohamed

“… In previous works, the neural models are trained classically by backpropagation (BP) algorithm. In this work, the sliding mode-backpropagation…”
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Replay as a Basis for Backpropagation Through Time in the Brain Autor Cheng, Huzi, Brown, Joshua W

“… The function of the replay events is a subject of active debate. Recurrent connectivity, computational simulations show, enables sequence learning when combined with a suitable learning algorithm such as backpropagation through time (BPTT…”
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A Deep Convolutional Gated Recurrent Unit for CT Image Reconstruction Autor Ikuta, Masaki, Zhang, Jun

“…Computed tomography (CT) is one of the most important medical imaging technologies in use today. Most commercial CT products use a technique known as the…”
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Uniformly Stable Backpropagation Algorithm to Train a Feedforward Neural Network Autor de Jesús Rubio, José, Angelov, Plamen, Pacheco, Jaime

“… It is true that in some research papers this problem has been considered, but this concerns continuous-time NN…”
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Backpropagation Algorithms for a Broad Class of Dynamic Networks Autor Orlando De Jesus, Hagan, M.T.

“…: backpropagation-through-time (BPTT) and real-time recurrent learning (RTRL). The structure of the LDDN framework enables an efficient implementation of both algorithms for arbitrary dynamic networks…”
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A general backpropagation algorithm for feedforward neural networks learning Autor Xinghuo Yu, Efe, M.O., Kaynak, O.

“…A general backpropagation algorithm is proposed for feedforward neural network learning with time varying inputs…”
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A simplification of the backpropagation-through-time algorithm for optimal neurocontrol Autor Bersini, H., Gorrini, V.

“…Backpropagation-through-time (BPTT) is the temporal extension of backpropagation which allows a multilayer neural network to approximate an optimal state-feedback control law provided some prior knowledge (Jacobian matrices…”
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A new Neuro-Fuzzy Inference System with Dynamic Neurons (NFIS-DN) for system identification and time series forecasting Autor Samanta, S., Suresh, S., Senthilnath, J., Sundararajan, N.

“… The antecedent and the consequent parameters of NFIS-DN are updated using a self-regulated backpropagation through time learning algorithm…”
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