Skip to content
Research Article Open access CC BY 4.0

Artificial Neural Network Model and Its Application in Signal Processing

Xianlu Pan, Ying Wang, Yu Qi

Asian Journal of Advanced Research and Reports · pp. 1–8 · Published 2 Jan 2023

10.9734/ajarr/2023/v17i1459

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.

Signal processing artificial neural network BP neural network CNN neural network RBF neural network

Cited by 4

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

4

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.