Spiking Neural P Systems for Time Series Analysis
Wang, Jun; Peng, Hong
Sold by GreatBookPrices, Columbia, MD, U.S.A.
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Add to basketSold by GreatBookPrices, Columbia, MD, U.S.A.
AbeBooks Seller since April 6, 2009
Condition: New
Quantity: Over 20 available
Add to basketAn up-to-date and accurate discussion of spiking neural P systems in time series analysis
In Spiking Neural P Systems for Time Series Analysis, the authors explore the fundamentals and the current states of both spiking neural P systems and time series analysis and examine the application models of time series analysis. You’ll also find walkthroughs of recurrent-like, echo-like, and reservoir computing models for time series prediction.
The book covers applications in time series analysis such as financial time series analysis, power load forecasting, photovoltaic power forecasting, and medical signal processing, and contains illustrative photographs and tables designed to improve reader understanding.
Readers will also find:
Perfect for scientists, researchers, postgraduates, lecturers, and teachers, Spiking Neural P Systems for Time Series Analysis will also benefit undergraduate students interested in advanced techniques for time series analysis.
Jun Wang, PhD, is a Professor in the School of Electrical Engineering and Electronic Information at Xihua University in Chengdu, China. Her research is focused on membrane computing, artificial intelligence, intelligence control. She has published over 90 scientific papers in international journals and conferences with an H-index of 35.
Hong Peng, PhD, is a Professor in the School of Computer and Software Engineering at Xihua University in Chengdu, China. His research interests include membrane computing, machine learning, pattern recognition. He has published over 230 scientific papers in international journals and conferences with an H-index of 42.
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