Circuit complexity and neural networks / (Record no. 73078)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03235nam a2200517 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 6267424 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220712204701.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 151223s1994 maua ob 001 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780262281249 |
| -- | ebook |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | |
| 100 1# - AUTHOR NAME | |
| Author | Parberry, Ian, |
| 245 10 - TITLE STATEMENT | |
| Title | Circuit complexity and neural networks / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 PDF (xxix, 270 pages) : |
| 490 1# - SERIES STATEMENT | |
| Series statement | Foundations of computing |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large amounts of input data. Circuit Complexity and Neural Networks addresses the important question of how well neural networks scale - that is, how fast the computation time and number of neurons grow as the problem size increases. It surveys recent research in circuit complexity (a robust branch of theoretical computer science) and applies this work to a theoretical understanding of the problem of scalability.Most research in neural networks focuses on learning, yet it is important to understand the physical limitations of the network before the resources needed to solve a certain problem can be calculated. One of the aims of this book is to compare the complexity of neural networks and the complexity of conventional computers, looking at the computational ability and resources (neurons and time) that are a necessary part of the foundations of neural network learning.Circuit Complexity and Neural Networks contains a significant amount of background material on conventional complexity theory that will enable neural network scientists to learn about how complexity theory applies to their discipline, and allow complexity theorists to see how their discipline applies to neural networks. |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6267424 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cambridge, Massachusetts : |
| -- | MIT Press, |
| -- | c1994. |
| 264 #2 - | |
| -- | [Piscataqay, New Jersey] : |
| -- | IEEE Xplore, |
| -- | [1994] |
| 336 ## - | |
| -- | text |
| -- | rdacontent |
| 337 ## - | |
| -- | electronic |
| -- | isbdmedia |
| 338 ## - | |
| -- | online resource |
| -- | rdacarrier |
| 588 ## - | |
| -- | Description based on PDF viewed 12/23/2015. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Logic circuits. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational complexity. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Neural networks (Computer science) |
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