Results 41 to 50 of about 53,216 (300)
On the Computational Power of RNNs
CoRR, 2019 Recent neural network architectures such as the basic recurrent neural network (RNN) and Gated Recurrent Unit (GRU) have gained prominence as end-to-end learning architectures for natural language processing tasks. But what is the computational power of such systems?
Samuel A. Korsky, Robert C. Berwick
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Design and research of high-speed channel estimation algorithm in OFDM system based on GCE-RNN algorithm [PDF]
Journal of Applied Research on Industrial EngineeringDue to the presence of Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI) in Orthogonal Frequency Division Multiplexing (OFDM) systems under high-velocity mobility conditions, channel estimation algorithms are challenged.
Ling Yao +2 more
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Advances in Distributed Computing and Artificial Intelligence Journal, 2021 Domain Name System (DNS) is a protocol for converting numeric IP addresses of websites into a human-readable form. With the development of technology, to transfer information, a method like DNS tunneling is used which includes data encryption into DNS ...
Dr. Gopal Sakarkar +6 more
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Low Precision RNNs: Quantizing RNNs Without Losing Accuracy
CoRR, 2017 Similar to convolution neural networks, recurrent neural networks (RNNs) typically suffer from over-parameterization. Quantizing bit-widths of weights and activations results in runtime efficiency on hardware, yet it often comes at the cost of reduced accuracy.
Supriya Kapur +2 more
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THE COMPARISON OF ARIMA AND RNN FOR FORECASTING GOLD FUTURES CLOSING PRICES
BarekengIn the financial markets, accurately forecasting the closing prices of gold futures is crucial for investors and analysts. Traditional methods like ARIMA (Autoregressive Integrated Moving Average) have been widely used for this purpose, particularly for ...
Windy Ayu Pratiwi +4 more
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W-RNN: News text classification based on a Weighted RNN
CoRR, 2019 7 pages, 10 ...
Dan Wang, Jibing Gong, Yaxi Song
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Modelling Time Series Data for Stock Prices Prediction Using Bidirectional Long Short-Term Memory
KnowbaseThe dynamic nature of stock markets, characterized by intricate patterns and sudden fluctuations, poses significant challenges to accurate price prediction. Traditional analytical methods are often unable to capture this complexity. This requires the use
Yenie Syukriyah, Adi Purnama
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Research progress on neural network algorithms for mixed gas detection in coal mines
Gong-kuang zidonghua, 2023 When coal mine gas sensors are used for mixed gas detection, there is cross interference between measurement signals. It is difficult to ensure detection accuracy.
JIAO Mingzhi +4 more
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cpmpercussion/gesture-rnn: Research Prototype Release
, 2017 <p>A release of gesture-rnn as a research prototype.</p ...
Charles Martin
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