A convolutional echo state network time sequence classification method based on a multi-head self-attention mechanism
A technology of echo state network and classification method, applied in the field of reserve pool computing and neural network research, can solve problems such as affecting model performance, inability to obtain performance, etc., to achieve the effect of reservation-free training
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Example Embodiment
[0051] Example
[0052] Such as figure 1 As shown, this embodiment discloses a multi-variable time series classification method of a convolution echo state network based on a multi-head self-attention mechanism. This method introduces a multi-head self-attention mapping mechanism in the traditional echo state network, and integrates multiple high-dimensional projections and high-dimensional feature global spatiotemporal coding on the input time series, and realizes the capture of complex time series features. Finally, a shallow layer The convolutional neural network achieves high-precision classification. The convolutional echo state network model based on the multi-head self-attention mechanism is a new type of reserve pool calculation model applied to time series classification. The model establishment process is as follows figure 2 As shown, including the following steps:
[0053] S1. Network initialization, determine the number of reserve pools, and initialize the internal p...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap