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Do-it-yourself Networking with LANtastic
This book assumes no previous networking knowledge, so it will provide definitions of new terms and nontechnical descriptions of network requirements. The reader will progress step-by-step through all phases of network setup.
Neural Networks for Pattern Recognition
Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.
Microsoft Windows 95 Resource Kit
Direct from the Windows 95 development team, this comprehensive book/disk combo is the most exhaustive source of technical information that computer professionals, advanced users, and many enthusiastic Windows users need to become experts on the latest release of Windows. It contains some of the most sought-after tips, tricks, and productivity secrets available.; 3 disks.
Artificial Neural Networks - ICANN 2010
This three volume set LNCS 6352, LNCS 6353, and LNCS 6354 constitutes the refereed proceedings of the 20th International Conference on Artificial Neural Networks, ICANN 2010, held in Thessaloniki, Greece, in September 20010. The 102 revised full papers, 68 short papers and 29 posters presented were carefully reviewed and selected from 241 submissions. The third volume is divided in topical sections on classification – pattern recognition, learning algorithms and systems, computational intelligence, IEM3 workshop, CVA workshop, and SOINN workshop.
Astrophysics Processes
Bridging the gap between physics and astronomy textbooks, this book provides step-by-step physical and mathematical development of fundamental astrophysical processes underlying a wide range of phenomena in stellar, galactic, and extragalactic astronomy. The book has been written for upper-level undergraduates and beginning graduate students, and its strong pedagogy ensures solid mastery of each process and application. It contains over 150 tutorial figures, numerous examples of astronomical measurements, and 201 exercises. Topics covered include the Kepler–Newton problem, stellar structure, binary evolution, radiation processes, special relativity in astronomy, radio propagation in the interstellar medium, and gravitational lensing. Applications presented include Jeans length, Eddington luminosity, the cooling of the cosmic microwave background (CMB), the Sunyaev–Zeldovich effect, Doppler boosting in jets, and determinations of the Hubble constant. This text is a stepping stone to more specialized books and primary literature. Password-protected solutions to the exercises are available to instructors at www.cambridge.org/9780521846561.
Computational Science and Its Applications – ICCSA 2021
The ten-volume set LNCS 12949 – 12958 constitutes the proceedings of the 21st International Conference on Computational Science and Its Applications, ICCSA 2021, which was held in Cagliari, Italy, during September 13 – 16, 2021. The event was organized in a hybrid mode due to the Covid-19 pandemic.The 466 full and 18 short papers presented in these proceedings were carefully reviewed and selected from 1588 submissions. The books cover such topics as multicore architectures, mobile and wireless security, sensor networks, open source software, collaborative and social computing systems and tools, cryptography, human computer interaction, software design engineering, and others. Part I of the set follows two general tracks: computational methods, algorithms, and scientific applications; high performance computing and networks.
Neural Networks and Learning Machines
For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Matlab codes used for the computer experiments in the text are available for download at: http: //www.pearsonhighered.com/haykin/ Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently.
The Future of Logistics
Based on 51 interviews with logistics CEOs, strategists, and scenario experts, Heiko A. von der Gracht shows that the logistics service industry draws a backward picture of scenario planning practices as compared to other industries.
