By B. Yegnanarayana
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Additional info for Artificial Neural Networks
This function bounds the output signal, and it is normally Activation Dynamics Models 43 a nondecreasing function of the activation value. 2a for a typical output function. Although the activation value is shown to have a large range, in practice the membrane potential has to be bounded due to limitation of the current carrying capacity of a membrane. Thus there is a limit to the operating range of a processing unit, which corresponds to the difference between the maximum and minimum activation values.
14 Introductipn 8. Explain the following pattern recognition issues with illustrations: (a) Pattern variability (b) Temporal patterns (c) Stability-plasticity dilemma 9. What are different methods for solving pattern recognition tasks? 10. What is the difficulty with the existing methods for solving natural pattern recognition problems? 11. Identifj. some difficult pattern recognition problems in the following areas: (a) Speech (b) Vision (c) Natural language processing 12. What are the issues at the architectural level of artificial neural networks?
In contrast, the purpose of neural network models is to provide a representation for the dynamics of an artificial network, incorporating features inspired by our understanding of the operation of the biological neural network. In other words, the neural network model is a mathematical model for analysis of gross characteristics of an artificial network. Typically, these models are described by an expression for the first order time derivative of the activation state for activation dynamics and an expression for the first order time derivative of the weight state for synaptic dynamics.