On the improvement of the real time recurrent learning algorithm for recurrent neural networks
β Scribed by M.W. Mak; K.W. Ku; Y.L. Lu
- Book ID
- 114297014
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 293 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0925-2312
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Williams and Zipser (1989) proposed two analoglte learning algorithms for fully recurrent networks. The first method is an exact gradient-following algorithm for problems where data consists of epochs. The second method, called the Real-Time Recurrent Learning ( RTRL ) algorithm, uses data descr
## Abstract Various types of neural networks have been proposed in previous papers for applications in hydrological events. However, most of these applied neural networks are classified as static neural networks, which are based on batch processes that update action only after the whole training da