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Dawson & Sons Ltd.,1923-199061 v. ;22 cmL'editore variaLingua ingleseBibliografiaLetteratura ingleseBibliografiaLetteratura americanaBibliografiaNilson, CharlesMarjory, RigbyMisenheimer, James B.Horden, JohnRoper, DerekSmith, MichaelErskine, ElizabethDe Marr, Mary JeanModern humanities research association.b1251785902-04-1413-11-03991004084919707536LE012 REF 016.82 ANN 4V. 412012000243064le012-E0.00-no 00000.i1295742213-11-03LE012 REF 016.82 ANN 5V. 512012000243071le012-E0.00-no 00000.i1295743413-11-03LE012 REF 016.82 ANN 6V. 612012000243088le012-E0.00-no 00000.i1295744613-11-03LE012 REF 016.82 ANN 7V. 712012000244191le012-E0.00-no 00000.i1295745813-11-03LE012 REF 016.82 ANN 8V. 812012000244207le012-E0.00-no 00000.i1295746x13-11-03LE012 REF 016.82 ANN 10V. 1012012000244214le012-E0.00-no 00000.i1295747113-11-03LE012 REF 016.82 ANN 11V. 1112012000244221le012-E0.00-no 00000.i1295748313-11-03LE012 REF 016.82 ANN 13V. 1312012000244238le012-E0.00-no 00000.i1295749513-11-03LE012 REF 016.82 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00000.i1295787213-11-03LE012 REF 016.82 ANN 51V. 5112012000244726le012-E0.00-no 00000.i1295788413-11-03LE012 REF 016.82 ANN 52V. 5212012000244733le012-E0.00-no 00000.i1295789613-11-03LE012 REF 016.82 ANN 53V. 5312012000244740le012-E0.00-no 00000.i1295790213-11-03LE012 REF 016.82 ANN 54V. 5412012000244757le012-E0.00-no 00000.i1295791413-11-03LE012 REF 016.82 ANN 55V. 5512012000244764le012-E0.00-no 00000.i1295792613-11-03LE012 REF 016.82 ANN 56V. 5612012000244771le012-E0.00-no 00000.i1295793813-11-03LE012 REF 016.82 ANN 57V. 5712012000244788le012-E0.00-no 00000.i1295794x13-11-03LE012 REF 016.82 ANN 58V. 5812012000244597le012-E0.00-no 00000.i1295795113-11-03LE012 REF 016.82 ANN 59V. 5912012000244603le012-E0.00-no 00000.i1295796313-11-03LE012 REF 016.82 ANN 60V. 6012012000244610le012-E0.00-no 00000.i1295797513-11-03LE012 REF 016.82 ANN 61V. 6112012000244627le012-E0.00-no 00000.i1295798713-11-03LE012 REF 016.82 ANN 9V. 912012000244634le012-E0.00-no 00000.i1295799913-11-03LE012 REF 016.82 ANN 34/AV. 3422012000244641le012-E0.00-no 00000.i1295800113-11-03LE012 REF 016.82 ANN 2V. 212012000244658le012-E0.00-no 00000.i1295801313-11-03LE012 REF 016.82 ANN 3V. 312012000244665le012-E0.00-no 00000.i1295802513-11-03LE012 REF 016.82 ANN 1V. 112012000244672le012-E0.00-no 00000.i1295803713-11-03Annual bibliography of English language and literature184016UNISALENTOle01213-11-03ma -enguik06205822nam 22006615 450 99654682090331620230612224555.0981-19-8008-X10.1007/978-981-19-8008-4(MiAaPQ)EBC7261462(Au-PeEL)EBL7261462(OCoLC)1382692524(DE-He213)978-981-19-8008-4(PPN)272261149(EXLCZ)992694041190004120230612d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierCommunication Principles for Data Science[electronic resource] /by Changho Suh1st ed. 2023.Singapore :Springer Nature Singapore :Imprint: Springer,2023.1 online resource (294 pages)Signals and Communication Technology,1860-4870Print version: Suh, Changho Communication Principles for Data Science Singapore : Springer,c2023 9789811980077 Includes bibliographical references.Preface -- Acknowledgements -- Part 1. Communication over the Gaussian channel -- Chapter 1.Overview of the book -- Chapter 2. A statistical model for additive noise channels -- Chapter 3. Additive Gaussian noise model -- Problem Set 1 -- Chapter 4. Optimal receiver: maximum A Posteriori (MAP) principle -- Chapter 5. Analysis of error probability -- Chapter 6. Multiple bits transmission via pulse amplitude modulation -- Problem Set 2 -- Chapter 7. Multi-shot communication -- Chapter 8. Repetition coding -- Chapter 9: Capacity of the additive white Gaussian noise channel -- Problem Set 3 -- Part 2. Communication over inter-symbol interference (ISI) channels -- Chapter 10. Signal conversion from discrete to continuous time (1/2) -- Chapter 11. Signal conversion from discrete to continuous time (2/2) -- Chapter 12. Optimal receiver architecture -- Problem Set 4 -- Chapter 13. Optimal receiver in ISI channels: maximum likelihood (ML) sequence detection -- Chapter 14. Optimal receiver in ISI channels: Viterbi algorithm -- Problem Set 5 -- Chapter 15.Orthogonal frequency division multiplexing (1/3) -- Chapter 16. Orthogonal frequency division multiplexing (2/3) -- Chapter 17. Orthogonal frequency division multiplexing (3/3) -- Problem Set 6 -- Part 3.Data science applications -- Chapter 18. Community detection as a communication problem -- Chapter 19. Community detection: ML principle -- Chapter 20. Community detection: An efficient algorithm -- Chapter 21. Community detection: Python implementation -- Problem Set 7 -- Chapter 22.Haplotype phasing as a communication problem -- Chapter 23. Haplotype phasing: ML principle -- Chapter 24: Haplotype phasing: An efficient algorithm. .This book introduces the basic principles underlying the design and analysis of the digital communication systems that have heralded the information revolution. One major goal of the book is to demonstrate the role of the digital communication principles in a wide variety of data science applications, including community detection, computational biology, speech recognition and machine learning. One defining feature of this book is to make an explicit connection between the communication principles and data science problems, as well as to succinctly deliver the “story” of how the communication principles play a role for trending data science applications. All the key “plots” involved in the story are coherently developed with the help of tightly coupled exercise problem sets, and the associated fundamentals are explored mostly from first principles. Another key feature is that it includes programming implementation of a variety of algorithms inspired by fundamentals, together with a brief tutorial of the used programming tools. The implementation is based on Python and TensorFlow. This book does not follow a traditional book-style organization, but is streamlined via a series of lecture notes that are intimately related, centered around coherent storylines and themes. It serves as a textbook mainly for a junior- or senior-level undergraduate course, yet is also suitable for a first-year graduate course. Readers benefit from having a good background in probability and random processes, and basic familiarity with Python. But the background can be supplemented by almost self-contained materials, as well as by numerous exercise problems intended for elaborating on non-trivial concepts. In addition, Part III for data science applications should provide motivation and insights to students and even professional scientists who are interested in the field.Signals and Communication Technology,1860-4870Artificial intelligence—Data processingDigital mediaComputer science—MathematicsMathematical statisticsSignal processingData ScienceDigital and New MediaProbability and Statistics in Computer ScienceSignal, Speech and Image Processing Artificial intelligence—Data processing.Digital media.Computer science—Mathematics.Mathematical statistics.Signal processing.Data Science.Digital and New Media.Probability and Statistics in Computer Science.Signal, Speech and Image Processing .381Suh Changho1310449MiAaPQMiAaPQMiAaPQBOOK996546820903316Communication Principles for Data Science3394561UNISA