Models Of Neurons And Perceptrons: Selected Problems And Challenges (studies In Computational Intelligence)
by Andrzej Bielecki /
2018 / English / PDF
5.6 MB Download
This book describes models of the neuron and multilayer neural
structures, with a particular focus on mathematical models. It
also discusses electronic circuits used as models of the neuron
and the synapse, and analyses the relations between the circuits
and mathematical models in detail.
This book describes models of the neuron and multilayer neural
structures, with a particular focus on mathematical models. It
also discusses electronic circuits used as models of the neuron
and the synapse, and analyses the relations between the circuits
and mathematical models in detail.
The first part describes the biological foundations and provides
a comprehensive overview of the artificial neural networks. The
second part then presents mathematical foundations, reviewing
elementary topics, as well as lesser-known problems such as
topological conjugacy of dynamical systems and the shadowing
property. The final two parts describe the models of the neuron,
and the mathematical analysis of the properties of artificial
multilayer neural networks.
The first part describes the biological foundations and provides
a comprehensive overview of the artificial neural networks. The
second part then presents mathematical foundations, reviewing
elementary topics, as well as lesser-known problems such as
topological conjugacy of dynamical systems and the shadowing
property. The final two parts describe the models of the neuron,
and the mathematical analysis of the properties of artificial
multilayer neural networks.Combining biological, mathematical and electronic approaches,
this multidisciplinary book it useful for the mathematicians
interested in artificial neural networks and models of the neuron,
for computer scientists interested in formal foundations of
artificial neural networks, and for the biologists interested in
mathematical and electronic models of neural structures and
processes.
Combining biological, mathematical and electronic approaches,
this multidisciplinary book it useful for the mathematicians
interested in artificial neural networks and models of the neuron,
for computer scientists interested in formal foundations of
artificial neural networks, and for the biologists interested in
mathematical and electronic models of neural structures and
processes.
