在工程、物理和生物医学领域，对数字信号处理的需求日益增长，寻求更为复杂且高效的解决方案。作者通过最新的研究工作，揭示了递归神经网络（Recurrent Neural Networks, RNNs）如何突破传统信号处理技术的界限，成为一种强大的预测工具。RNNs被重新定义为一种大型的、互联的、非线性自适应滤波器，其独特之处...
Crucially, our framework also offers a number of extensions that address a broad range of use cases beyond univariate time series prediction. For example, we show how predictive densities over the occurrence of critical events within a predictive horizon can be inferred from our forecasts. Whereas ...
Recurrent Neural Networks for Prediction, a comprehensive work by Danilo P. Mandic and Jonathon A. Chambers, was published in 2001 by John Wiley & Sons Inc. This influential book delves into the intricacies of recurrent neural networks (RNNs) specifically tailored for prediction tasks....
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs,这是一篇2017年发表在顶级期刊NIPS上的文章,作者通过发现传统RNN/LSTM网络的不足,提出了一种新的网络结构PredRNN,并且为这一网络结构设计了一种新的RNN单元(ST-LSTM)。由于博
Recurrent neural networks for prediction : learning algorithms, architectures, and stability / Danilo P. Mandic, Jonathon A. Chambers. p. cm - - (Wiley series in adaptive and learning systems for signal processing, communications, and control) Includes bibliographical references and index. ISBN 0-...
We used group normalization for its stability and independence from the batch size. We present a deep comparison of the structure, flexibility, flow ... M Benhaddi,J Ouarzazi 被引量: 0发表: 2021年 加载更多来源图书 Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and St...
Graphical illustration of the Robust Dual Recurrent Neural Networks (RDRNN) for financial time series prediction. Problem Formulation 假设存在n+1个时间序列,使用其中一个序列作为目标序列,其他序列作为外部序列(exogenous series)。使用\textbf{X}=\left\{ \text{x}_1,\text{x}_2,...,\text{x}_T \...
Recurrent Neural Networks as Local Models for Time Series Prediction "Local models" (Walter, J., et al. International Joint Conference on Neural Networks, vol. 1. (1990) 589-594), consists on dividing the data into homogeneous clusters by Vector Quantization (VQ (Gray, R. M., and Neuhoff...
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