Artificial Neural Networks :: Essays Papers

Artificial Neural Networks Artificial neural networks be systems implemented on computer systems as specialized hardw ar or sophisticated software that loosely model the learning and remembering functions of the humans intellect. They are an attempt to simulate the multiple layers of processing elements in the brain, c all(prenominal)ed neurons. These elements are implemented in such a way so that the layers scum bag learn from prior experience and remember their outputs. In this way, the system asshole learn to recognize certain patterns and situations and apply these to certain priorities and output grab results. These types of neural networks stand be used in m any valuable situations such as priority in an emergency room, for financial assistance, and any type of pattern recognition such as handwritten or text-to-speech recognition. The most basic elements of a neural network, the artificial neurons, are copy after the neurons of the brain. The real neuron is comp osed of tetrad parts the dendrites, soma, axon, and the synapse. The dendrites cop input from other neurons synapses, the soma processes the in figureation received, the axon carries the action electromotive force which fires the neuron when a threshold is breached, and the synapse is where the neuron sends its output, which are in the form of neurotransmitters, to the dendrites of other neurons. Each neuron in the human brain can connect with up to 200,000 other neurons. The power and processing of the human brain comes from multitude of these basic components and the many thousands of connections between them. The artificial neurons simulate the four basic functions of the real neuron. The artificial neuron is much transparentr than the neuron of the brain. It takes inputs mediocre as the real neuron but also multiplies these inputs by a weight value. Then they are sent to a processing whole which does what it needs to do to the value and then sends this value to the outp ut path. In the simplest case the products of these values are simply summed and then put finished a transfer process and output. This is the basic building block of all artificial neural networks, although there are many different implementations of this simple block and fundamental differences which allow for different artificial networks to be built. The major concerns of the developer is the design of the neural network system.