Artificial Neural Networks

Artificial neural networks

An artificial neuron.
The basic behavior of an artificial neural network is determined by the dot product (weighted sum) operator in each neuron.
This also has a geometric interpretation.
The dot product of A and B is the magnitude (vector length) of vector A by the magnitude of vector B by the cosine of the angle between them.



 Dot product video.



Statistical properties of the dot product.


The central limit theorem.

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  1. Further information.

    The Weighted Sum:
    https://archive.org/details/the-weighted-sum

    A frozen neural network:
    https://archive.org/details/afrozenneuralnetwork

    The Walsh Hadamard transform:
    https://archive.org/details/whtebook-archive

    The Walsh Hadamard transform (short):
    https://archive.org/details/short-wht

    Activation weight switching (Beyond ReLU):
    https://archive.org/details/activation-weight-switching

    Zero curvature initialisation of neural networks:
    https://archive.org/details/zero-curvatue

    SwitchNet4 neural network:
    https://discourse.processing.org/t/switch-net-4-neural-network/33220





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