✦ LIBER ✦

A learning model for oscillatory networks

✍ Scribed by Jun Nishii

Publisher: Elsevier Science
Year: 1998
Tongue: English
Weight: 267 KB
Volume: 11
Category: Article
ISSN: 0893-6080
DOI: 10.1016/s0893-6080(97)00074-9

No coin nor oath required. For personal study only.

✦ Synopsis

A learning model for coupled oscillators is proposed. The proposed learning rule takes a simple form by which the intrinsic frequencies of the component oscillators and the coupling strength between them are changed according to the effects of the input signals on the dynamics of the oscillator. In the learning mode, each component oscillator receives a teacher signal of desired phase and frequency, and a desired parameter set for generating the desired pattern is acquired by the proposed learning rule. It is known that the basic locomotor patterns of many living bodies are generated by coupled neural oscillators. The proposed learning rule could be a learning model used by such neural systems to acquire an adequate parameter set for generating a desired locomotor pattern.

📜 SIMILAR VOLUMES

A learning algorithm for oscillatory cel

A learning algorithm for oscillatory cellular neural networks

✍ C.Y. Ho; H. Kurokawa 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 566 KB

We present a cellular type oscillatory neural network for temporal segregation of stationary input patterns. The model comprises an array of locally connected neural oscillators with connections limited to a 4-connected neighborhood. The architecture is reminiscent of the wellknown cellular neural n

A network learning model with GERT analy

A network learning model with GERT analysis

✍ P.H. Randolph; R.D. Ringeisen 📂 Article 📅 1974 🏛 Elsevier Science 🌐 English ⚖ 539 KB

A model for oscillatory kinetic systems

✍ Joseph Dreitlein; Marie-Luce Smoes 📂 Article 📅 1974 🏛 Elsevier Science 🌐 English ⚖ 677 KB

Mathematical learning models and neurona

Mathematical learning models and neuronal networks

✍ E. Pfaffelhuber 📂 Article 📅 1973 🏛 Elsevier Science 🌐 English ⚖ 801 KB

Artificial Neural Networks for Modeling

Artificial Neural Networks for Modeling Knowing and Learning in Science

✍ Wolff-Michael Roth 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 94 KB 👁 2 views

Recent neurobiological evidence suggests that environmentally derived activity plays a central role in regulating neuronal growth and neuronal connectivity. Artificial neural networks with distributed representations display many features of knowing and learning that are known from biological intell

Nested effects models for learning signa

Nested effects models for learning signaling networks from perturbation data

✍ Holger Fröhlich; Achim Tresch; Tim Beißbarth 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 465 KB 👁 1 views

## Abstract Targeted gene perturbations have become a major tool to gain insight into complex cellular processes. In combination with the measurement of downstream effects __via__ DNA microarrays, this approach can be used to gain insight into signaling pathways. __Nested Effects Models__ were firs