Abstract
A new algorithm is presented for blind identification of moving average (MA) models using the 1-D slice of its fourth-order cumulants and the autocorrelation functions. The proposed algorithm utilizes the BPSK signals as MA models input that is an independent and identically distributed (i.i.d) process. Our algorithm is compared with Giannakis algorithm. Simulations verify the good performance of the proposed algorithm.
Keywords: Blind identification, higher-order statistics, MA models, BPSK signals
Related Books
Challenges and Opportunities for Deep Learning Applications in Industry 4.0
Recent Advances in IoT and Blockchain Technology
Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining
Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments Part II
Machine Learning and Its Application: A Quick Guide for Beginners
Computational Intelligence For Data Analysis
Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
Advanced Computing Techniques: Implementation, Informatics and Emerging Technologies
How to Design Optimization Algorithms by Applying Natural Behavioral Patterns
Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments (Part I)
2