Spiking Neural P Systems: Theory, Applications and Implementations by Gexiang Zhang , Sergey Verlan , Tingfang Wu , Francis George C. Cabarle , Jie Xue , David Orellana-Martín , Jianping Dong , Luis Valencia-Cabrera , Mario J. Pérez-Jiménez
English | PDF EPUB (True) | 2024 | 435 Pages | ISBN : 9819792819 | 54.1 MB
Spiking neural P systems represent a significant advancement in the field of membrane computing, drawing inspiration from the communication patterns observed in neurons. Since their inception in 2006, these distributed and parallel neural-like computing models have gained popularity and emerged as important tools within the membrane computing area. As a key branch of the third generation of artificial neural networks, a fascinating research area of artificial intelligence, spiking neural P systems offer a captivating blend of theoretical elegance and practical utility. Their efficiency, Turing completeness, and real-life application characteristics, including interpretability and suitability for large-scale problems, have positioned them at the forefront of contemporary research in membrane computing and artificial intelligence.
