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Neural Networks
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Neural Networks mimic the pattern of human learning to solve many difficult tasks of data management and pattern recognition. By configuring virtual neural networks that function like the human brain, computers can perform tasks at greater speeds and with increased flexibility of application. These networks are capable of offering invaluable insights into the vast information stockpiles that are common today. The human brain is constructed of a vast network of interconnected entities. These entities function together to enable us learn and to perform a diverse array of tasks. The neuron is responsible for this learning process and it is made up of three main parts the dendrites, the soma, and the axon. The dendrites form the input network that consists of branches, which connect to tens of thousands of other neurons. This interconnectedness is what determines our adaptability and creativity. The next element of the neuron is the Soma. This is the processing element that determines at which threshold the neuron will respond. A constant flow of chemical signals causes stimulation of an output once the integrated signal reaches a certain threshold value. When a signal is finally generated, it is conducted down the Axon, and then continues to another dendrite or to the muscle cells. (“Nervous System”, Encyclopedia Britannica) During the learning process, adjustments to the response threshold values are made. These adjustments cause the Soma to become more excitable.
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