Intelligent Engineering Systems through Artificial Neural Networks, Volume 20
13 Monitoring Artificial Neural Network Performance Degradation under Network Damage
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Recently a number of research groups presented transistor-based designs exhibiting behavior similar to biological synapses, facilitating creation of a tangible artificial neuron. Hardware neural networks would possess great advantages in information processing tasks that are inherently parallel, such as image processing, require learning, such as handwriting recognition, or in an environment where the processing unit might be susceptible to physical damage. A number of different possibilities for realization of hardware neural networks currently exist. This paper presents analysis of performance degradation of various architectures of artificial neural networks when subjected to neural damage. An analysis of un-optimized and optimized, feed-forward...