The Net Advance of Physics:
NEURAL NETWORKS
NEURAL NETS:
General: Textbooks:
Gurney 96/06;
General:
Biology-Derived Algorithms in Engineering Optimization
by Xin-She Yang [2005]
From Neuron to Neural Networks dynamics
by B. Cessac and M. Samuelides [2006/09]
The Physics of Living Neural Networks
by Jean-Pierre Eckmann et al. [
Physics Reports 449
, 54 (2007)]
Complex and Adaptive Dynamical Systems: A Primer
by Claudius Gros [Springer, 2008]
A Tutorial in Connectome Analysis: Topological and Spatial Features of Brain Networks
by Marcus Kaiser [2011/05]
Type: CLIFFORD:
Introduction to Clifford's Geometric Algebra
by Eckhard Hitzer [
Journal of the Society of Instrument and Control Engineers 51
, 338 (2012)]
Type: CONVOLUTIONAL:
Recent Advances in Convolutional Neural Networks
by Jiuxiang Gu et al. [2015/12]
Type: RANDOM RECURRENT:
Random Recurrent Neural Networks Dynamics
by M. Samuelides and B. Cessac [2006/12]
Type: SELF-ORGANISING MAP:
Advances in Self Organising Maps
by Marie Cottrell and Michel Verleysen [
Neural Networks 19
, 721 (2006)]
Aspects: ATTRACTORS:
Parisi 94/12;
Re: DYNAMICAL SYSTEMS:
Neural Networks as dynamical systems
by Bruno Cessac [2009/01]
Re: INFORMATION THEORY:
Applications of Information Theory to Analysis of Neural Data
by Simon R. Schultz et al. [2015/01]
Estimating Information-Theoretic Quantities
by Robin A. A. Ince et al. [2015/01]
Re: PERCOLATION:
The Physics of Living Neural Networks
by Jean-Pierre Eckmann et al. [
Physics Reports 449
, 54 (2007)]
THE NET ADVANCE OF PHYSICS