|
The author discusses interesting connections between special types of Boolean functions and the simplest types of neural networks. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks.
Discrete Mathematics of Neural Networks: Selected Topics (Siam Monographs on Discrete Mathematics and Applications) Автор: Martin Anthony Год: 1996 |
Introduction to quantum mechanics Автор: A. C. Phillips Год: 2003 |
Introduction to Quantum Mechanics Автор: A. C. Phillips Год: 2003 |
Introduction to Quantum Mechanics Автор: A. C. Phillips Год: 2003 |
Introduction to Quantum Mechanics Автор: A. C. Phillips Год: 2003 |
Discrete mathematics of neural networks: selected topics Автор: Martin Anthony Год: 1987 |