Back-propagation network (BPN). Student : Dah-Sheng Lee Professor: Hahn-Ming Lee Date:20 September 2003. Outline. What is a Neural Network ? Artificial Neural Network (ANN) property Back-propagation network (BPN) Reference. What is a Neural Network ?.
Student : Dah-Sheng Lee
Professor: Hahn-Ming Lee
Date:20 September 2003
A biological neuron may have as many as 10,000 different inputs, and may send its output (the presence or absence of a short-duration spike) to many other neurons. Neurons are wired up in a 3-dimensional pattern. Real brains, however, are orders of magnitude more complex than any artificial neural network so far considered.
The dendrites are extensions of a neuron which connect to other neurons to form a neural network, while synapses are a gateway which connects to dendrites that come from other neurons.
A biological neuron may thus be connected to other neurons as well as accepting connections from other neurons, and so we have the basis of a network.
Through those connections, electrical pulses are transmitted, and information is carried in the timing and the frequency with which these pulses are emitted.
So, our neuron receives information from other neurons, processes it and then relays this information to other neurons.
Bidirectional Associative Memory(BAM),
ANN(Annealed Neural Network)
The network model “BPN” is
(Special case: no hidden layer)
an input pattern and calculate the network response.
output of the network, and by using 1* and 2* all the local
errors can be computed
producing the adequate response for all the training pattern,
continue step 2 through 4
Fredric M. Ham; Ivica Kostanic;
McGRAW-HILL INTERNATIONAL EDITION, 2001