Results 161 to 170 of about 233,583 (184)

Deep Tree Echo State Networks

2018 International Joint Conference on Neural Networks (IJCNN), 2018
This work proposes a first study, through empirical assessment, of a deep recursive Neural Network (RecNN) architecture for tree structured data exploiting the efficient design of the Echo State Network (ESN) framework. Three benchmark tasks for trees allow us to assess the potentiality of the novel Deep Tree ESN (DeepTESN) model with respect to the ...
Gallicchio, Claudio, Micheli, Alessio
openaire   +2 more sources

Growing Echo-State Network With Multiple Subreservoirs

IEEE Transactions on Neural Networks and Learning Systems, 2017
An echo-state network (ESN) is an effective alternative to gradient methods for training recurrent neural network. However, it is difficult to determine the structure (mainly the reservoir) of the ESN to match with the given application. In this paper, a growing ESN (GESN) is proposed to design the size and topology of the reservoir automatically ...
Junfei, Qiao, Fanjun, Li, Honggui, Han, Wenjing, Li   +3 more
openaire   +2 more sources

FPGA-Based Echo-State Networks

2019
The hardware implementation of Echo State Networks (ESN) can be applied to situations where a quick response is needed in relation to how a certain signal will evolve. This is due to the possibility of connecting the ESN’s neurons in parallel, which accelerates the calculation process considerably. In this article, we present a proposal for the compact
Erik S. Skibinsky-Gitlin, Miquel L. Alomar, Vincent Canals, Christiam F. Frasser, Eugeni Isern, Fabio Galán-Prado, Alejandro Morán, Miquel Roca, Josep L. Rosselló   +8 more
openaire   +1 more source

Decoupled echo state networks with lateral inhibition

Neural Networks, 2007
Building on some prior work, in this paper we describe a novel structure termed the decoupled echo state network (DESN) involving the use of lateral inhibition. Two low-complexity implementation schemes, namely, the DESN with reservoir prediction (DESN + RP) and DESN with maximum available information (DESN + MaxInfo), are developed: (1) In the ...
Xue, Yanbo, Yang, Le, Haykin, Simon
openaire   +2 more sources

Modular state space of echo state network

Neurocomputing, 2013
Echo state network (ESN) mainly consists of a reservoir with a large number of neurons that are randomly connected and a linear readout (output) that is easily adapted. From this point, the reservoir will reconstruct the input signals in the high-dimensional state space.
Qian-Li Ma, Wei-Biao Chen
openaire   +1 more source

Onion Echo State Networks

Echo state networks (ESNs) are a class of recurrent neural networks (RNNs) designed according to the Reservoir Computing (RC) approach, where the dynamical part of the model is initialized and left untrained. The reservoir’s topology and spectral properties both play an important role in producing an informative encoding of the input sequence.
Domenico Tortorella, Alessio Micheli
openaire   +1 more source

Echo State Networks

2022
openaire   +1 more source

A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction

Energy, 2023
Sujan Ghimire, Thong Nguyen-Huy, Mohanad S Al-Musaylh   +2 more
exaly  

Discrete-time dynamic graph echo state networks

Neurocomputing, 2022
Alessio Micheli, Domenico Tortorella
exaly  

Architectural and Markovian factors of echo state networks

Neural Networks, 2011
Claudio Gallicchio, Alessio Micheli
exaly