Extreme learning machine (ELM) was proposed by Guang-Bin and Qin-Yu, which was aim to train single-hidden layer feedforward networks (SLFNs). Their solutions are dependent on the parameter initialization and the complexity of the feature space, so they are more likely to converge at local extrema. ![]() However, gradient based algorithms do not always come up with global best solution. BP was widely used in many domains because it is easy to understand and simple to implement. Traditional training algorithms are often based on gradient, like back propagation (BP). To train the network is to determine the weights in its layers that makes it best approximates the data. It is weights that decide how a neuron processes input signals to give out output signals. And each connection delivers an important parameter called weight. A neuron may have lots of connections to neurons of its former layer and later layer. The connection was defined as relation between neurons of different layers. Neurons within a neural network are often organized in different layers. In neural network, a neuron, also called perception, receives input signals from former neurons and sends out output signals to later neurons. As a kind of machine learning method, a typical neural network consists of neurons, connections, and weights. ![]() Neural network was inspired by biological neural network and its basic structure mimics the nerve system in human brain. ![]() Neural network, which usually refers to artificial neural network, was firstly proposed in last century for a history of more than 70 years.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |