Computer Science/Neural Networks/A Simple Network
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Any neural network consists of neurons and synapses which interconnect neurons. Every synapse has its own synaptic weight.
These neurons and synapses change their mechanism of interconnection dynamically on each interaction with the environment and become more efficient and intelligent through the process of learning the environment itself. There are five basic learning processes which have been developed to simulate neural networks on a computing device. They enable this device to react and learn in ways that in a simplified way imitates living organisms.
[edit] The learning processes are:
- Error-Correction Learning
- Memory Based Learning
- Competitive Learning
- Hebbian Learning
- Boltzmann Learning
i want to brief description of above learning process
