Abstract
A variant of the Hopfield network, called the modified Hopfield network is formulated. This network which consists of two mutually recurrent networks has more free parameters than the well-known Hopfield network. Stability analysis of this network is presented. The analysis is carried out in the time domain with an application of the Lyapunov method and robust control Lyapunov function. The current flow in the network is treated as a "control". This "controller" is shown to guarantee "a practically stabilizing control". Analysis of the Hopfield network is also included for completion.
| Original language | American English |
|---|---|
| Journal | Proceedings of the 37th IEEE Conference on Decision and Control, 1998 |
| DOIs | |
| State | Published - Jan 1 1998 |
Keywords
- Hopfield Neural Nets
- Lyapunov Method
- Lyapunov Methods
- Modified Hopfield Neural Networks
- Mutually Recurrent Networks
- Neurocontrollers
- Practically Stabilizing Control
- Robust Control
- Robust Control Lyapunov Function
- Robustness Analysis
- Time Domain
- Time-Domain Analysis
Disciplines
- Aerospace Engineering
- Mechanical Engineering
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