✦ LIBER ✦

Generalised scheme for optimal learning in recurrent neural networks

✍ Scribed by Shanmukh, K.; Venkatesh, Y.V.

Book ID: 114457416
Publisher: The Institution of Electrical Engineers
Year: 1995
Tongue: English
Weight: 486 KB
Volume: 142
Category: Article
ISSN: 1350-245X
DOI: 10.1049/ip-vis:19951679

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Learning in recurrent neural networks

✍ Halbert White 📂 Article 📅 1991 🏛 Elsevier Science 🌐 English ⚖ 85 KB

Bayesian learning for recurrent neural n

Bayesian learning for recurrent neural networks

✍ Michel Crucianu; Romuald Boné; Jean-Pierre Asselin de Beauville 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 126 KB

Recurrent Neural Networks for Structural

Recurrent Neural Networks for Structural Optimization

✍ Azadeh Parvin; Gursel Serpen 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 130 KB

A posteriori real-time recurrent learnin

A posteriori real-time recurrent learning schemes for a recurrent neural network based nonlinear predictor

✍ Mandic, D.P.; Chambers, J.A. 📂 Article 📅 1998 🏛 The Institution of Electrical Engineers 🌐 English ⚖ 656 KB

A realtime learning algorithm for recurr

A realtime learning algorithm for recurrent neural networks

✍ Tadasu Uchiyama; Katsunori Shimohara 📂 Article 📅 1991 🏛 John Wiley and Sons 🌐 English ⚖ 438 KB

Effective learning in recurrent max–min

Effective learning in recurrent max–min neural networks

✍ Loo-Nin Teow; Kia-Fock Loe 📂 Article 📅 1998 🏛 Elsevier Science 🌐 English ⚖ 208 KB

Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real-valued domains. As such, neural networks that employ max-min activation functions have been a subject of interest in recent years. Since max-min functions are not strictly dif