官术网_书友最值得收藏!

An overview of neural networks

Neural networks represent a brain metaphor for information processing. These models are biologically inspired rather than an exact replica of how the brain actually functions. Neural networks have been shown to be very promising systems in many forecasting applications and business classification applications due to their ability to learn from the data.

The artificial neural network learns by updating the network architecture and connection weights so that the network can efficiently perform a task. It can learn either from available training patterns or automatically learn from examples or input-output relations. The learning process is designed by one of the following:

  • Knowing about available information
  • Learning the paradigm--having a model from the environment
  • Learning rules--figuring out the update process of weights
  • Learning the algorithm--identifying a procedure to adjust weights by learning rules

There are four basic types of learning rules:

  • Error correction rules
  • Boltzmann
  • Hebbian
  • Competitive learning
主站蜘蛛池模板: 赞皇县| 曲阳县| 阿勒泰市| 黄浦区| 南召县| 嵩明县| 广宁县| 陕西省| 嫩江县| 上思县| 民勤县| 永嘉县| 贞丰县| 古交市| 封开县| 崇义县| 灵山县| 罗定市| 车致| 南通市| 高州市| 庆云县| 明溪县| 高青县| 包头市| 香港 | 成都市| 酉阳| 称多县| 绥化市| 手游| 临夏市| 潼南县| 沈丘县| 巨鹿县| 成都市| 离岛区| 璧山县| 环江| 柳河县| 聂荣县|