Spiking Neural P Systems 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.

• About the Authors ixPreface xiAcknowledgments xiiiAcronyms xv1 Introduction 11.1 Background 11.2 Membrane Computing 21.3 Spiking Neural P Systems 41.4 Time Series Analysis 71.5 Organization of Chapters 102 Spiking Neural P Systems 172.1 Introduction 172.2 Preliminaries 182.3 Spiking Neural P Systems 192.4 Spiking Neural P Systems with Extended Rules 222.5 Spiking Neural P Systems with Autapses 252.6 Nonlinear Spiking Neural P Systems 283 Recurrent-like Models for Time-series Forecasting 333.1 Introduction 333.2 Recurrent Neural Networks 343.3 LSTM-SNP Model 373.4 GSNP Model 443.5 NSNP-AU Model 514 Echo-like Models for Time Series Forecasting 654.1 Introduction 654.2 Echo State Networks 664.3 Echo-like Spiking Neural P Model 674.4 Echo-like Feedback Spiking Neural P Model 764.5 Deep Echo-like Spiking Neural P Model 835 Reservoir Computing Models for Time Series Classification 975.1 Introduction 975.2 Preliminaries 985.3 Basic Models 1005.4 Improved Models 1055.5 Model Evaluation 1096 Financial Time Series Analysis 1156.1 Stock Market Index Prediction 1156.2 Exchange Rate Price Prediction 1266.3 Crude Oil Price Prediction 1377 Power Load Forecasting and Photovoltaic Power Forecasting 1557.1 Power Load Forecasting 1557.2 Photovoltaic Power Forecasting 1678 Medical Signal Processing 1958.1 Introduction 1958.2 Methodology 1968.3 Model Evaluation 204Index 211