國立虎尾科技大學 |

Advanced spiking neural P systems = models and applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advanced spiking neural P systems/ by Hong Peng, Jun Wang.
其他題名:	models and applications /
作者:	Peng, Hong.
其他作者:	Wang, Jun.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xiv, 297 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Machine Learning. -
電子資源:	https://doi.org/10.1007/978-981-97-5280-5
ISBN:	9789819752805

Advanced spiking neural P systems = models and applications /
Peng, Hong.

Advanced spiking neural P systemsmodels and applications /[electronic resource] :by Hong Peng, Jun Wang. - Singapore :Springer Nature Singapore :2024. - xiv, 297 p. :ill., digital ;24 cm. - Computational intelligence methods and applications,2510-1773. - Computational intelligence methods and applications..

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.

ISBN: 9789819752805

Standard No.: 10.1007/978-981-97-5280-5doiSubjects--Topical Terms:

1137723
Machine Learning.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.382

Advanced spiking neural P systems = models and applications /
LDR:02891nam a22003495a 4500 001 1134700
003 DE-He213
005 20240823124816.0
006 m d
007 cr nn 008maaau
008 241213s2024 si s 0 eng d
020 $a 9789819752805 $q (electronic bk.)
020 $a 9789819752799 $q (paper)
024 7 $a 10.1007/978-981-97-5280-5 $2 doi
035 $a 978-981-97-5280-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.N37
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.382 $2 23
090 $a QA76.9.N37 $b P398 2024
100 1 $a Peng, Hong. $e editor. $3 1358260
245 1 0 $a Advanced spiking neural P systems $h [electronic resource] : $b models and applications / $c by Hong Peng, Jun Wang.
260 $a Singapore : $c 2024. $b Springer Nature Singapore : $b Imprint: Springer,
300 $a xiv, 297 p. : $b ill., digital ; $c 24 cm.
347 $a text file $b PDF $2 rda
490 1 $a Computational intelligence methods and applications, $x 2510-1773
505 0 $a 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.
520 $a 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.
650 2 4 $a Machine Learning. $3 1137723
650 2 4 $a Natural Language Processing (NLP) $3 1211064
650 2 4 $a Image Processing. $3 669795
650 2 4 $a Theory of Computation. $3 669322
650 2 4 $a Models of Computation. $3 1365746
650 1 4 $a Artificial Intelligence. $3 646849
650 0 $a Membrane computers. $3 1456269
700 1 $a Wang, Jun. $3 674981
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
830 0 $a Computational intelligence methods and applications. $3 1115380
856 4 0 $u https://doi.org/10.1007/978-981-97-5280-5
950 $a Computer Science (SpringerNature-11645)