Input layer Neural Networks
In the last month I started to work for a project that involves Artificial Intelligence, to be more specific Artificial Neural Networks. If you want to find out more about neural networks, here is a link:
The structure can be simplified into a few classes:
- Neuron – Like a neuron in the nervous system in the human body it is the main component of our structure. It has a few properties like Input Function, Activation Level, Output.
- Layer – This will be a structure that contains more neurons. In this project we will have 3 type of layers. Input layer, the layer that will forward data that will be processed by the following layer or layers (depending on the complexity of the application) is the hidden layer. This layer or layers will process the input data and forward it to the output layer which should give us the result.
- Link – this class is used by the Neuron as input. This will contain a neuron from the previous layer and a synaptic weight. In case that the Layer is input layer, than we will only have one input value and a synaptic weight of 1 so that it will not alter the result.
- Activation – This class is also use by the Neuron in order to calculate input value, activation level.
Source: Maier Walter
The new exchange calculator, or, An assistant to checking calculations of Indian exchange on England, at rates progressing by 1/32 of a penny, from 1s. 10d. to 2s. 2d. per rupee
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