A qualitative analysis is developed for continuous-time neural networks subjected to random pure structural variations. Simple algebraic conditions are established for both structural exponential stability of x = 0 of the neural network and for estimates of its domain of attraction. Bounds on motion
β¦ LIBER β¦
Analysis and synthesis of continuous-time hysteretic neural networks
β Scribed by Kenya Jin'no; Toshimichi Saito
- Book ID
- 112079574
- Publisher
- John Wiley and Sons
- Year
- 1993
- Tongue
- English
- Weight
- 429 KB
- Volume
- 76
- Category
- Article
- ISSN
- 1042-0967
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In this paper, we prove that any finite time trajectory of a given n-dimensional dynamical system can be approximately realized by the internal state of the output units of a continuous time recurrent neural network with n output units, some hidden units, and an appropriate initial condition. The es