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▼a9789819752805▼9978-981-97-5280-5 |
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▼a10.1007/978-981-97-5280-5▼2doi |
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▼a221008 |
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▼aQ334-342 |
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▼aPeng, Hong.▼eauthor.▼4aut▼4http://id.loc.gov/vocabulary/relators/aut |
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▼aAdvanced Spiking Neural P Systems▼h[electronic resource] :▼bModels and Applications /▼cby Hong Peng, Jun Wang. |
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▼a1st ed. 2024. |
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▼aSingapore :▼bSpringer Nature Singapore :▼bImprint: Springer,▼c2024. |
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▼aXIV, 297 p. 136 illus., 107 illus. in color.▼bonline resource. |
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▼atext▼btxt▼2rdacontent |
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▼acomputer▼bc▼2rdamedia |
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▼aonline resource▼bcr▼2rdacarrier |
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▼atext file▼bPDF▼2rda |
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▼aComputational Intelligence Methods and Applications,▼x2510-1773 |
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▼aChapter 1. Introduction -- Chapter 2. Spiking Neural P Systems and Variants -- Chapter 3. Computational Completeness -- Chapter 4. Fuzzy Spiking Neural P Systems -- Chapter 5.Time Series Forecasting -- Chapter 6. Image Processing -- Chapter 7. Sentiment Analysis -- Chapter 8. Fault Diagnosis. |
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▼aMembrane computing is a class of distributed and parallel computing models inspired by living cells. Spiking neural P systems are neural-like membrane computing models, representing an interdisciplinary field between membrane computing and artificial neural networks, and are considered one of the third-generation neural networks. Models and applications constitute two major research topics in spiking neural P systems. The entire book comprises two parts: models and applications. In the model part, several variants of spiking neural P systems and fuzzy spiking neural P systems are introduced. Subsequently, their computational completeness is discussed, encompassing digital generation/accepting devices, function computing devices, and language generation devices. This discussion is advantageous for researchers in the fields of membrane computing, biologically inspired computing, and theoretical computer science, aiding in understanding the distributed computing model of spiking neural P systems. In the application part, the application of spiking neural P systems in time series prediction, image processing, sentiment analysis, and fault diagnosis is examined. This offers a novel method and model for researchers in artificial intelligence, data mining, image processing, natural language processing, and power systems. Simultaneously, it furnishes engineering and technical personnel in these fields with a powerful, efficient, reliable, and user-friendly set of tools and methods. . |
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▼aArtificial intelligence. |
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▼aComputer science. |
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▼aImage processing. |
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▼aNatural language processing (Computer science). |
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▼aMachine learning. |
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▼aArtificial Intelligence. |
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▼aModels of Computation. |
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▼aTheory of Computation. |
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▼aImage Processing. |
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▼aNatural Language Processing (NLP). |
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▼aMachine Learning. |
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▼aWang, Jun.▼eauthor.▼4aut▼4http://id.loc.gov/vocabulary/relators/aut |
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▼aSpringerLink (Online service) |
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▼tSpringer Nature eBook |
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▼iPrinted edition:▼z9789819752799 |
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▼iPrinted edition:▼z9789819752812 |
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▼iPrinted edition:▼z9789819752829 |
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▼aComputational Intelligence Methods and Applications,▼x2510-1773 |
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▼uhttps://doi.org/10.1007/978-981-97-5280-5 |
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▼aZDB-2-SCS |
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▼aZDB-2-SXCS |
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▼aComputer Science (SpringerNature-11645) |
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▼aComputer Science (R0) (SpringerNature-43710) |