We have located links that may give you full text access.
Design of deep echo state networks.
In this paper, we provide a novel approach to the architectural design of deep Recurrent Neural Networks using signal frequency analysis. In particular, focusing on the Reservoir Computing framework and inspired by the principles related to the inherent effect of layering, we address a fundamental open issue in deep learning, namely the question of how to establish the number of layers in recurrent architectures in the form of deep echo state networks (DeepESNs). The proposed method is first analyzed and refined on a controlled scenario and then it is experimentally assessed on challenging real-world tasks. The achieved results also show the ability of properly designed DeepESNs to outperform RC approaches on a speech recognition task, and to compete with the state-of-the-art in time-series prediction on polyphonic music tasks.
Full text links
Trending Papers
A Personalized Approach to the Management of Congestion in Acute Heart Failure.Heart International 2023
Potential Mechanisms of the Protective Effects of the Cardiometabolic Drugs Type-2 Sodium-Glucose Transporter Inhibitors and Glucagon-like Peptide-1 Receptor Agonists in Heart Failure.International Journal of Molecular Sciences 2024 Februrary 21
The Effect of Albumin Administration in Critically Ill Patients: A Retrospective Single-Center Analysis.Critical Care Medicine 2024 Februrary 8
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app