✦ LIBER ✦

The use of random weights for the training of multilayer networks of neurons with Heaviside characteristics

✍ Scribed by T. Downs; R.J. Gaynier

Book ID: 103929417
Publisher: Elsevier Science
Year: 1995
Tongue: English
Weight: 709 KB
Volume: 22
Category: Article
ISSN: 0895-7177
DOI: 10.1016/0895-7177(95)00180-a

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Evaluation of the Simplex method for tra

Evaluation of the Simplex method for training simple multilayer neural networks

✍ M. Dornier; B. Heyd; M. Danzart 📂 Article 📅 1998 🏛 Springer-Verlag 🌐 English ⚖ 725 KB

Use of multilayer networks for the recog

Use of multilayer networks for the recognition of phonetic features and phonemes

✍ Yoshua Bengio; Renato De Mori 📂 Article 📅 1989 🏛 John Wiley and Sons 🌐 English ⚖ 879 KB

Sliding mode algorithm for training mult

Sliding mode algorithm for training multilayer artificial neural networks

✍ Parma, G.G.; Menezes, B.R.; Braga, A.P. 📂 Article 📅 1998 🏛 The Institution of Electrical Engineers 🌐 English ⚖ 259 KB

On the Use of Dynamic Bayesian Networks

On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles

✍ Eldawlatly, Seif; Zhou, Yang; Jin, Rong; Oweiss, Karim G. 📂 Article 📅 2010 🏛 MIT Press 🌐 English ⚖ 584 KB

Derivation of the multilayer perceptron

Derivation of the multilayer perceptron weight constraints for direct network interpretation and knowledge discovery

✍ M.L. Vaughn 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 171 KB

This paper examines the multilayer perceptron (MLP) network from a hidden layer decision region perspective and derives the output layer and hidden layer weight constraints that the network must satisfy in performing a general classification task. This provides a foundation for direct knowledge disc

Signal transmission in random spike trai

Signal transmission in random spike trains with applications to the statocyst neurons of the lobster

✍ Knox, Charles K. 📂 Article 📅 1970 🏛 Springer-Verlag ⚖ 908 KB