Artificial Neural Network Model and Its Application in Signal Processing
Xianlu Pan *
Qingdao University of Science and Technology, Qingdao-266061, China.
Ying Wang
Qingdao University of Science and Technology, Qingdao-266061, China.
Yu Qi
Qingdao University of Science and Technology, Qingdao-266061, China.
*Author to whom correspondence should be addressed.
Abstract
The human brain is a powerful image and pattern recognition processor, and its basic processing element is neurons. Synapses are weighted interconnections between neurons, allowing learning and communication between neurons. Artificial neural network (ANN) is an information processing system established by simulating the structure and logical thinking mode of human brain. The uniqueness of ANN is that it is nonlinear and trained to complete processing tasks in a way similar to human brain learning. It is particularly suitable for processing signals sent by various sensors, signals sent by communication devices, and other signals that are difficult to identify. This paper introduces the origin, types and research progress of neural networks, and summarizes the application research progress of neural networks in the field of signal processing. This paper introduces the origin, types and research progress of ANN, and summarizes the application research progress of ANN in the field of signal processing.
Keywords: Signal processing, artificial neural network, BP neural network, CNN neural network, RBF neural network