A Proposed DOA Estimation Technique Based on Wavelet Packet Decomposition for Fading Channel in MIMO Systems

2019 ◽  
Author(s):  
Aksha Mushtaq ◽  
Garima Mahendru
Keyword(s):  
Fading Channel ◽  
Mimo Systems ◽  
Wavelet Packet ◽  
Doa Estimation ◽  
Wavelet Packet Decomposition ◽  
Estimation Technique

scholarly journals Examining the Applicability of Wavelet Packet Decomposition on Different Forecasting Models in Annual Rainfall Prediction

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 1997
Author(s):  
Hua Wang ◽  
Wenchuan Wang ◽  
Yujin Du ◽  
Dongmei Xu
Keyword(s):  
Wavelet Packet ◽  
Moving Average ◽  
Back Propagation ◽  
Processing Technique ◽  
Annual Rainfall ◽  
Wavelet Packet Decomposition ◽  
Rainfall Forecasting ◽  
Promising Alternative ◽  
Forecasting Models ◽  
Precipitation Prediction

Accurate precipitation prediction can help plan for different water resources management demands and provide an extension of lead-time for the tactical and strategic planning of courses of action. This paper examines the applicability of several forecasting models based on wavelet packet decomposition (WPD) in annual rainfall forecasting, and a novel hybrid precipitation prediction framework (WPD-ELM) is proposed coupling extreme learning machine (ELM) and WPD. The works of this paper can be described as follows: (a) WPD is used to decompose the original precipitation data into several sub-layers; (b) ELM model, autoregressive integrated moving average model (ARIMA), and back-propagation neural network (BPNN) are employed to realize the forecasting computation for the decomposed series; (c) the results are integrated to attain the final prediction. Four evaluation indexes (RMSE, MAE, R, and NSEC) are adopted to assess the performance of the models. The results indicate that the WPD-ELM model outperforms other models used in this paper and WPD can significantly enhance the performance of forecasting models. In conclusion, WPD-ELM can be a promising alternative for annual precipitation forecasting and WPD is an effective data pre-processing technique in producing convincing forecasting models.

scholarly journals Adaptive frequency scaled wavelet packet decomposition for frog call classification

2016 ◽  
Vol 32 ◽  
pp. 134-144 ◽  
Author(s):  
Jie Xie ◽  
Michael Towsey ◽  
Jinglan Zhang ◽  
Paul Roe
Keyword(s):  
Wavelet Packet ◽  
Wavelet Packet Decomposition ◽  
Call Classification
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