Reservoir computing has emerged in the last decade as an alternative to gradient descent methods for training recurrent neural networks. Echo State Network (ESN) is one of the key reservoir computing “flavors”. While being practical, conceptually simple, and easy to implement, ESNs require some experience and insight to achieve the hailed good performance in many tasks. Here we present practical techniques and recommendations for successfully applying ESNs, as well as some more advanced application-specific modifications.
Swipe to navigate through the chapters of this book
Please log in to get access to this content
To get access to this content you need the following product:
- A Practical Guide to Applying Echo State Networks
- Springer Berlin Heidelberg
- Sequence number
- Chapter number