A Special Criteria to Globally Exponentially Stability for Discrete-Time Recurrent Neural Networks
| Autor: | Ji Min Yuan, Wei Gen Wu, Xin Yin |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Quantitative Biology::Neurons and Cognition
Basis (linear algebra) General Engineering Stability (learning theory) Winner-take-all Matrix (mathematics) medicine.anatomical_structure Recurrent neural network Exponential growth Control theory medicine Neuron Discrete time recurrent neural networks Mathematics |
| Zdroj: | Advanced Materials Research. :293-298 |
| ISSN: | 1662-8985 |
| Popis: | On average, each of the 1011 neurons has 1000 synaptic connections with other neurons in reality. In order to simulate a biological genuine model, the stability of a special discrete-time recurrent neural networks model that every neuron only has one input neuron is considered. And a main result is obtained. It provides some theoretical basis for the application. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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