Artificial Neural Networks Architecture
What is Artificial Neural Networks Architecture ?
This is a topic that I get vastly fascinating. Technological advances are running forward as if there's the burning on their butt, and they don't appear to be slowing down. Google stated that it was translating its strategy from `` Mobile-first '' to "AI-first ", corporations , e.g., that I represent producing Quantum computers which might ease this development of Artificial Neural Networks (Ann ) and Deep Learning, Tesla is showing this way towards sustainable 21st-century life (solar ceiling tiles, house battery-packs, electrical vehicles etc) . And I'm not yet gonna move into VR, Arkansas, and man.
Artificial neural networks are a technology based on studies of the brain and nervous system as depicted in Fig.
These networks emulate a biological neural network but they use a reduced set of concepts from biological neural systems. Specifically, ANN models simulate the electrical activity of the brain and nervous system. Processing elements (also known as either a neurode or perceptron) are connected to other processing elements. Typically the neurodes are arranged in a layer or vector, with the output of one layer serving as the input to the next layer and possibly other layers. A neurode may be connected to all or a subset of the neurodes in the subsequent layer, with these connections simulating the synaptic connections of the brain. Weighted data signals entering a neurode simulate the electrical excitation of a nerve cell and consequently the transference of information within the network or brain. The input values to a processing element, in, are multiplied by a connection weight, wn,m, that simulates the strengthening of neural pathways in the brain. It is through the adjustment of the connection strengths or weights that learning is emulated in ANNs.
Similarity
to biological systems: the field of ANN imitates the human brain functioning
and at the same time tries to achieve better performance in hard problem
solving. An ANN is an abstraction and a simplification of biological neural
networks.
There are
different biological neurons in different parts of the brain, however, their
basic structure is the same . Dendrites transmit input signals to the neuron
and an axon transmits the output signal over the synapses towards the dendrites
of other neurons. Although highly simplified, ANN models suffice for useful
modeling and analyses which enable better understanding of processes in the
brain.
Ads go here
Nice
ReplyDeleteNice
ReplyDeleteOsm
ReplyDelete