A neuron is an information-processing unit that is fundamental to the operation of a neural network. The block diagram of Fig. 1.5 shows the model of a neuron, which forms the basis for designing (artificial)neural networks. Here we identify three basic elements of the neuronal model:
1. A set of synapses or connecting links, each of which is characterized by a weight or strength of its own. Specifically, a signal xj at the input of synapes j connected to neuron k is multiplied by the synaptic weight wkj. It is important to make a note of the manner in which the subscripts of the synaptic weight wkj are written; the first subscript refers to the neuron in question and the second subscript refers to the input end of the synapse to which the weight refers. Unlike a synapse in the brain, the synaptic weight of an artificial neuron may lie in a range that includes negative as well as positive values.
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