Mathematical Perspectives on Neural Networks
Paul Smolensky · Michael C. Mozer · David E. Rumelhart
2013. g. maijs · Psychology Press
5,0star
1 atsauksmereport
E-grāmata
880
Lappuses
family_home
Piemērota
info
reportAtsauksmes un vērtējumi nav pārbaudīti. Uzzināt vairāk
Par šo e-grāmatu
Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests on a breadth of mathematical background which even few specialists possess. In a format intermediate between a textbook and a collection of research articles, this book has been assembled to present a sample of these results, and to fill in the necessary background, in such areas as computability theory, computational complexity theory, the theory of analog computation, stochastic processes, dynamical systems, control theory, time-series analysis, Bayesian analysis, regularization theory, information theory, computational learning theory, and mathematical statistics.
Mathematical models of neural networks display an amazing richness and diversity. Neural networks can be formally modeled as computational systems, as physical or dynamical systems, and as statistical analyzers. Within each of these three broad perspectives, there are a number of particular approaches. For each of 16 particular mathematical perspectives on neural networks, the contributing authors provide introductions to the background mathematics, and address questions such as:
* Exactly what mathematical systems are used to model neural networks from the given perspective?
* What formal questions about neural networks can then be addressed?
* What are typical results that can be obtained? and
* What are the outstanding open problems?
A distinctive feature of this volume is that for each perspective presented in one of the contributed chapters, the first editor has provided a moderately detailed summary of the formal results and the requisite mathematical concepts. These summaries are presented in four chapters that tie together the 16 contributed chapters: three develop a coherent view of the three general perspectives -- computational, dynamical, and statistical; the other assembles these three perspectives into a unified overview of the neural networks field.
Mathematical models of neural networks display an amazing richness and diversity. Neural networks can be formally modeled as computational systems, as physical or dynamical systems, and as statistical analyzers. Within each of these three broad perspectives, there are a number of particular approaches. For each of 16 particular mathematical perspectives on neural networks, the contributing authors provide introductions to the background mathematics, and address questions such as:
* Exactly what mathematical systems are used to model neural networks from the given perspective?
* What formal questions about neural networks can then be addressed?
* What are typical results that can be obtained? and
* What are the outstanding open problems?
A distinctive feature of this volume is that for each perspective presented in one of the contributed chapters, the first editor has provided a moderately detailed summary of the formal results and the requisite mathematical concepts. These summaries are presented in four chapters that tie together the 16 contributed chapters: three develop a coherent view of the three general perspectives -- computational, dynamical, and statistical; the other assembles these three perspectives into a unified overview of the neural networks field.
Vērtējumi un atsauksmes
5,0
1 atsauksme
Par autoru
Paul Smolensky, Michael C. Mozer, David E. Rumelhart
Novērtējiet šo e-grāmatu
Izsakiet savu viedokli!
Informācija lasīšanai
Viedtālruņi un planšetdatori
Instalējiet lietotni Google Play grāmatas Android ierīcēm un iPad planšetdatoriem/iPhone tālruņiem. Lietotne tiks automātiski sinhronizēta ar jūsu kontu un ļaus lasīt saturu tiešsaistē vai bezsaistē neatkarīgi no jūsu atrašanās vietas.
Klēpjdatori un galddatori
Varat klausīties pakalpojumā Google Play iegādātās audiogrāmatas, izmantojot datora tīmekļa pārlūkprogrammu.
E-lasītāji un citas ierīces
Lai lasītu grāmatas tādās elektroniskās tintes ierīcēs kā Kobo e-lasītāji, nepieciešams lejupielādēt failu un pārsūtīt to uz savu ierīci. Izpildiet palīdzības centrā sniegtos detalizētos norādījumus, lai pārsūtītu failus uz atbalstītiem e-lasītājiem.
