SONET/SDH Demystified | By Steven Shepard
Publisher: McGraw-Hill Professional | Pages: 378 | Publication Date: 2001-07-18 | ISBN: 0071376186 | PDF | 2.90 MB
Clear explanations of SONET (Synchronous Optical Network), the industry standard for high speed transmission over optical fiber, for the non-engineer *Provides detailed SONET case studies and business models *Includes coverage of DWDM (Dense Wavelength Division Multiplexing) and WDM (Wavelength Division Multiplexing
Clear explanations of SONET (Synchronous Optical Network), the industry standard for high speed transmission over optical fiber, for the non-engineer.
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CISCO CCNA 4.0 Exploration and Discovery | 156 MB
The Cisco CCNA® Exploration curriculum provides a comprehensive overview of networking.
from fundamentals to advanced applications and services. It is based on a top-down approach to networking that is popular in many colleges and universities. This course emphasizes theoretical concepts and practical application, while providing opportunities for students to gain the skills and hands-on experience needed to design, install, operate, and maintain networks in small-to-medium businesses, as well as enterprise and service provider environments.
CCNA Exploration offers in-depth theory, challenging labs, and a detailed overview of protocol operations. It is designed for students with advanced problem-solving and analytical skills, such as degree candidates in engineering, math, or science, or for working professionals who would like to advance their careers or gain certification. CCNA Exploration was designed to be integrated into technology curricula or continuing education programs at postsecondary institutions such as technical schools, colleges, and universities.
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Implementing Service Quality in IP Networks
Wiley | ISBN: 047084793X | 312 pages | March 31, 2003 | PDF | 1 Mb
While more and more data is shifted from circuit-switched to packet-switched networks, the users of these networks expect a smooth, continuously unproblematic service (unrelated to the amount of data transported). Therefore, the reliability of a network as well as the satisfaction of its users relies largely on Quality of Service (QoS). Service quality through resource management in IP networks will ensure that sufficient resources are available to fulfil the delay of applications and packet loss requirements.
This year several books on QoS from the angle of operators/engineers have been published HOWEVER, none of these titles tackle the management side of the problem. This book shows how to determine quality requirements of services, it discusses and considers the various means of allocating network resources and of supervising the service quality. Furthermore, it explores strategies for allocating network resources and their relation to revenue or operator utility as well as service allocation optimization. The book concludes with a Nokia case study that illustrates the previously mentioned concepts.
Essential reading for networking professionals wishing to understand service quality management in IP networks, as well as students needing to understand principles and basic techniques of service quality management.
Neural Networks Theory
Springer; 1 edition | ISBN: 3540481249 | 420 pages | September 14, 2007 | PDF | 17 MB
“Neural Networks Theory is a major contribution to the neural networks literature. It is a treasure trove that should be mined by the thousands of researchers and practitioners worldwide who have not previously had access to the fruits of Soviet and Russian neural network research. Dr. Galushkin is to be congratulated and thanked for his completion of this monumental work; a book that only he could write. It is a major gift to the world.”
Robert Hecht Nielsen, Computational Neurobiology, University of California, San Diego
“Professor Galushkins monograph has many unique features that in totality make his work an important contribution to the literature of neural networks theory. He and his publisher deserve profuse thanks and congratulations from all who are seriously interested in the foundations of neural networks theory, its evolution and current status.”
Lotfi Zadeh, Berkeley, Founder of Fuzziness
“Professor Galushkin, a leader in neural networks theory in Russia, uses mathematical methods in combination with complexity theory, nonlinear dynamics and optimization, concepts that are solidly grounded in Russian tradition. His theory is expansive: covering not just the traditional topics such as network architecture, it also addresses neural continua in function spaces. I am pleased to see his theory presented in its entirety here, for the first time for many, so that the both theory he developed and the approach he took to understand such complex phenomena can be fully appreciated.”
Sun-Ichi Amari, Director of RIKEN Brain Science Institute RIKEN
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