Models and Applications Peng, Hong. creator author. aut http://id.loc.gov/vocabulary/relators/aut Wang, Jun. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text si 2024 1st ed. 2024. monographic eng

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access XIV, 297 p. 136 illus., 107 illus. in color. online resource. Membrane 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. . Chapter 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. by Hong Peng, Jun Wang. Artificial intelligence Computer science Image processing Natural language processing (Computer science) Machine learning Artificial Intelligence Models of Computation Theory of Computation Image Processing Natural Language Processing (NLP) Machine Learning Q334-342 TA347.A78 9789819752805 https://doi.org/10.1007/978-981-97-5280-5 https://doi.org/10.1007/978-981-97-5280-5 240823 20251030112908.0 978-981-97-5280-5