04151nam a22006255i 4500 978-981-97-5280-5 DE-He213 20251030112908.0 cr nn 008mamaa 240823s2024 si | s |||| 0|eng d 9789819752805 978-981-97-5280-5 10.1007/978-981-97-5280-5 doi Q334-342 TA347.A78 UYQ bicssc COM004000 bisacsh UYQ thema Peng, Hong. author. aut http://id.loc.gov/vocabulary/relators/aut 70340 Advanced Spiking Neural P Systems [electronic resource] : Models and Applications / by Hong Peng, Jun Wang. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XIV, 297 p. 136 illus., 107 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Computational Intelligence Methods and Applications, 2510-1773 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. 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. . Artificial intelligence. 58441 Computer science. 58552 Image processing. Natural language processing (Computer science). 65131 Machine learning. 55059 Artificial Intelligence. 58441 Models of Computation. 66444 Theory of Computation. 67552 Image Processing. Natural Language Processing (NLP). 66164 Machine Learning. 55059 Wang, Jun. author. aut http://id.loc.gov/vocabulary/relators/aut 71684 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819752799 Printed edition: 9789819752812 Printed edition: 9789819752829 Computational Intelligence Methods and Applications, 2510-1773 70583 https://doi.org/10.1007/978-981-97-5280-5 ZDB-2-SCS ZDB-2-SXCS 62679 62679