754 views
06 Dec 09 Network Protocols: Signature Edition
Network Protocols: Signature Edition (Mcgraw-Hill Signature Series)
McGraw-Hill Companies | ISBN: 0070466033 | September 1998 | 953 pages | PDF | 7 MB
Without protocols, the Internet as well as LANs, WANs, and other networks would stop dead. And without this bestselling handbook, network managers would lack the only convenient, single-source reference to the plethera of a protocol that govern cyberspace. » » » »
505 views
06 Dec 09 Wireless Networking: Know It All
Wireless Networking: Know It All (Newnes Know It All)
Newnes | 2007-09-12 | ISBN: 0750685824 | 576 pages | PDF | 10 MB
One-stop information source for embedded engineers to learn the theory and real-world application of creating embedded networking systems, with detailed fully functional design examples, schematics, and source code. » » » »
133 views
04 Dec 09 Network Theory and Filter Design: Vasudev K. Aatre
Network Theory and Filter Design: Vasudev K. Aatre
John Wiley and Sons Inc | ISBN: 0470202254 | 1986-12-02 | PDF (OCR) | 476 pages | 11.6 Mb
An attempt has been made to include two aspects of network theory, analysis and synthesis under a single cover. Basics of network theory - formulation and solution of network equilibrium equtaions, network theorems and natural frequencies, multiterminal networks, state models - are all discussed. » » » »
207 views
04 Dec 09 CCSP: Cisco Certified Security Professional Certification All-in-One Exam Guide
Publisher: McGraw-Hill Osborne Media | ISBN: 0072226919 | edition 2003 | PDF | 984 pages | 12,25 mb
All-in-One is all you need! This authoritative reference offers complete coverage of all material on CCSP exams SECUR (Exam 642-501), CSPFA (Exam 642-511), CSVPN (Exam 642-511), CSIDS (Exam 642-531), and CSI (Exam 642-541). » » » »
68 views
01 Dec 09 Hebbian Learning and Negative Feedback Networks
Springer; 1 edition (December 1, 2004) | English | 1852338830 | 383 pages | PDF | 6.75 MB
The central idea of Hebbian Learning and Negative Feedback Networks is that artificial neural networks using negative feedback of activation can use simple Hebbian learning to self-organise so that they uncover interesting structures in data sets. » » » »
80 views
25 Nov 09 Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation)
Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation): Nikolay Nikolaev, Hitoshi Iba,
Springer | ISBN: 0387312390 | 2006-05-03 | PDF (OCR) | 316 pages | 15.5 Mb
This book delivers theoretical and practical knowledge for developing algorithms that infer linear and non-linear multivariate models, providing a methodology for inductive learning of polynomial neural network models (PNN) from data. » » » »
