ABSTRACT
Donald Hebb’s rule says that the changes in the strength of synaptic connections are proportional to the correlation in the firing of the two connecting neurons. The strength of the synapse between the neurons that responded to hearing the bell and those that caused the salivation reflex was enough that just hearing the bell caused the salivation neurons to fire in sympathy. The axons divide into connections to many other neurons, connecting to each of these neurons in a synapse. Each neuron is typically connected to thousands of other neurons, so that it is estimated that there are about 100 trillion synapses within the brain. The Perceptron is nothing more than a collection of McCulloch and Pitts neurons together with a set of inputs and some weights to fasten the inputs to the neurons. Machine learning algorithms tend to learn much more effectively if the inputs and targets are prepared for analysis before the network is trained.
