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1

Decoding your dreams. New York: H. Holt, 1988.

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2

Decoding your dreams. London: Unwin Hyman, 1989.

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3

Langs, Robert. Decoding your dreams. London: Unwin Paperbacks, 1990.

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4

F, Gesteland Raymond y SpringerLink (Online service), eds. Recoding: Expansion of Decoding Rules Enriches Gene Expression. New York, NY: Springer Science+Business Media, LLC, 2010.

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5

Berghoff, Hartmut. Decoding Modern Consumer Societies. New York: Palgrave Macmillan, 2012.

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6

Decoding the past: The psychohistorical approach. New Brunswick, N.J., U.S.A: Transaction Publishers, 1996.

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7

Decoding the past: The psychohistorical approach. Berkeley: University of California Press, 1985.

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8

Tanzi, Rudolph E. Decoding darkness: The search for the genetic causes of Alzheimer's disease. Cambridge, Mass: Perseus Publishing, 2000.

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9

Tanzi, Rudolph E. Decoding darkness: The search for the genetic causes of Alzheimer's disease. Cambridge, Mass: Perseus Pub., 2000.

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10

B, Parson Ann, ed. Decoding darkness: The search for the genetic causes of Alzheimer's disease. Cambridge, Mass: Perseus Publ., 2000.

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11

1971-, Kim Saejoon, ed. Fundamentals of codes, graphs, and iterative decoding. Boston: Kluwer Academic Publishers, 2003.

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12

Keyser, Amber. Decoding genes with Max Axiom, super scientist. Mankato, Minn: Capstone Press, 2010.

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13

Keyser, Amber. Decoding genes with Max Axiom, super scientist. Mankato, Minn: Capstone Press, 2010.

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14

Decoding gender in science fiction. New York: Routledge, 2002.

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15

Fridell, Ron. Decoding life: Unraveling the mysteries of the genome. Minneapolis, Minn: Lerner Publications, 2005.

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16

Haynes, John Earl. Venona: Decoding Soviet espionage in America. New Haven, Conn: Yale University Press, 1999.

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17

Harvey, Klehr, ed. Venona: Decoding Soviet espionage in America. New Haven, Conn: Yale University Press, 1999.

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18

Biogenealogy: Decoding the psychic roots of illness freedom from the ancestral origins of disease. Rochester, Vt: Healing Arts Press, 2006.

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19

Tomlinson, Martin. Error-Correction Coding and Decoding: Bounds, Codes, Decoders, Analysis and Applications. Cham: Springer Nature, 2017.

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20

The isis thesis: A study decoding 870 ancient Egyptian signs. Gaylord, MI: Envision Editions, Ltd., 2004.

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21

Shishkin, Aleksey. Methods of digital processing and speech recognition. ru: INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1904325.

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The monograph discusses the theory, algorithms and practical methods of implementing digital processing and recognition of speech signals. The basics of mathematical analysis of digital signals necessary for speech processing are presented. The acoustic theory of speech formation with the construction of a general discrete model is briefly described. The main characteristic features of speech signals, as well as methods of their isolation are considered. Hidden Markov models and the architecture of traditional recognition systems based on them are described in detail. Weighted finite converters used to increase the efficiency and speed up the process of decoding acoustic signals are considered. The main architectures of artificial neural networks and examples of integrated (end-to-end) speech recognition systems based on them are presented. It is intended for students, postgraduates, researchers and specialists dealing with speech signal processing, pattern recognition and artificial intelligence.
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22

author, Mark David 1973 y Greenfield, Jeff, author of foreword, eds. Dog whistles, walk-backs, and Washington handshakes: Decoding the jargon, slang, and bluster of American political speech. Lebanon, NH: ForeEdge, 2014.

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23

Shipovskaya, Lyudmila. Music as an element of spiritual culture is a powerful factor of integration and universalization of the entire spiritual life of society. ru: INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/2052437.

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The monograph is devoted to the ability of music in different phases of its functioning (creation, performance, perception) to convincingly demonstrate the associative and code principles of consciousness — mutual connection, induction and "translation" (encoding and decoding) of its various aspects, structures (in particular, emotional and rational) and levels (for example, individual and general, concrete and abstract). It is highlighted that music unites people, helps to resist disunity, indifference, feelings of loss and uselessness in the big world. It is revealed that the unifying power of music is manifested not only when a huge auditorium lives in one breath, when it freezes at once or suddenly bursts into a storm of applause in a single burst; a person feels this power, even if the sounds flow from a television or radio receiver. Spiritual culture should be addressed only to a person, it has a beneficial effect on a person's behavior, his work activity and the whole way of life. The socio-cultural significance of musical art is dramatically increasing in the context of a radical transformation of our society. It should ensure the assimilation of spiritual values that form the foundation of human life. It is intended for the widest audience of readers — from students of children's music schools and art schools to students of humanities faculties of universities and lovers of musical art.
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24

Tharp, D. Scott. Decoding Privilege. Taylor & Francis Group, 2021.

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25

Tharp, D. Scott. Decoding Privilege. Taylor & Francis Group, 2021.

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26

Lamel, Lori y Jean-Luc Gauvain. Speech Recognition. Editado por Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0016.

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Speech recognition is concerned with converting the speech waveform, an acoustic signal, into a sequence of words. Today's approaches are based on a statistical modellization of the speech signal. This article provides an overview of the main topics addressed in speech recognition, which are, acoustic-phonetic modelling, lexical representation, language modelling, decoding, and model adaptation. Language models are used in speech recognition to estimate the probability of word sequences. The main components of a generic speech recognition system are, main knowledge sources, feature analysis, and acoustic and language models, which are estimated in a training phase, and the decoder. The focus of this article is on methods used in state-of-the-art speaker-independent, large-vocabulary continuous speech recognition (LVCSR). Primary application areas for such technology are dictation, spoken language dialogue, and transcription for information archival and retrieval systems. Finally, this article discusses issues and directions of future research.
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27

Bronson, Po y Arvind Gupta. Decoding the World. Headline Publishing Group, 2020.

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28

Bronson, Po y Arvind Gupta. Decoding the World. Wildfire, 2021.

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29

Decoding the World. Headline Publishing Group, 2020.

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30

Decoding Liberation. Routledge, 2007.

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31

Uharriet, Thomas E. Billy Shears Acrostical Decoding. MACCA CORP., 2018.

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32

Uharriet, Thomas E. Billy Shears Acrostical Decoding. CreateSpace Independent Publishing Platform, 2014.

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33

Decoding the Language of Genetics. Cold Spring Harbor Laboratory Press, 2015.

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34

Ozturk, Munir, Khalid Rehman Hakeem, Adeel Malik y Fazilet Vardar-Sukan. Plant Bioinformatics: Decoding the Phyta. Springer, 2017.

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35

Ozturk, Munir, Khalid Rehman Hakeem, Adeel Malik y Fazilet Vardar-Sukan. Plant Bioinformatics: Decoding the Phyta. Springer, 2018.

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36

Niedenthal, Paula M., Adrienne Wood, Magdalena Rychlowska y Sebastian Korb. Embodied Simulation in Decoding Facial Expression. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190613501.003.0021.

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The present chapter explores evidence for the role of embodied simulation and facial mimicry in the decoding of facial expression of emotion. We begin the chapter by reviewing evidence in favor of the hypothesis that mimicking a perceived facial expression helps the perceiver achieve greater decoding accuracy. We report experimental and correlational evidence in favor of the general effect, and we also examine the assertion that facial mimicry influences perceptual processing of facial expression. Finally, after examining the behavioral evidence, we look into the brain to explore the neural circuitry and chemistry involved in embodied simulation of facial expressions of emotion.
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37

Gesteland, Raymond F. y John F. Atkins. Recoding: Expansion of Decoding Rules Enriches Gene Expression. Springer, 2011.

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38

Gesteland, Raymond F. y John F. Atkins. Recoding: Expansion of Decoding Rules Enriches Gene Expression. Springer, 2012.

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39

Tanzi, Rudolph E., Rudolph Tanzi y Ann B. Parson. Decoding Darkness: The Search for the Genetic Causes of Alzheimer's Disease. Basic Books, 2001.

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40

Tanzi, Rudolph E. y Ann B. Parson. Decoding Darkness: The Search for the Genetic Causes of Alzheimer's Disease. Basic Books, 2008.

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41

Decoding Racial Ideology in Genomics. Lexington Books/Fortress Academic, 2016.

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42

Williams, Johnny E. Decoding Racial Ideology in Genomics. Lexington Books/Fortress Academic, 2016.

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43

Williams, Johnny E. y Joseph L. Graves Jr. Decoding Racial Ideology in Genomics. Lexington Books, 2018.

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44

Nader, Ralph y Mark Green. Fake President: Decoding Trump's Gaslighting, Corruption, and General Bullsh*t. Skyhorse Publishing Company, Incorporated, 2019.

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45

Fake President: Decoding Trump's Gaslighting, Corruption, and General Bullsh*t. Skyhorse Publishing Company, Incorporated, 2019.

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46

Wicker, Stephen B. y Saejoon Saejoon Kim. Fundamentals of Codes, Graphs, and Iterative Decoding. Springer London, Limited, 2006.

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47

Wicker, Stephen B. y Saejoon Saejoon Kim. Fundamentals of Codes, Graphs, and Iterative Decoding. Springer, 2013.

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48

Çelik, Arzu y Mathias F. Wernet. Decoding Neural Circuit Structure and Function: Cellular Dissection Using Genetic Model Organisms. Springer International Publishing AG, 2017.

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49

Çelik, Arzu y Mathias F. Wernet. Decoding Neural Circuit Structure and Function: Cellular Dissection Using Genetic Model Organisms. Springer, 2018.

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50

Cyber Victimology: Decoding Cyber Crime Victimization. Taylor & Francis Group, 2025.

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