Signal processing is an important field in engineering sciences and mathematics that deals with the analysis and transformation of various signals such as audio, video, transaction and electronic signals. In this article, we will review the basic concepts of signal processing, methods, and its applications.
In fact, signal processing is a very broad and multidisciplinary field that deals with the analysis and transformation of signals as functions of temporal or spatial variation. This field is used as a basic tool in various fields and plays an important role in analyzing and understanding signal data. Below are some of the fields of application of this field:
Telecommunications: In communication and telecommunications, signals are usually information used to transmit information from one point to another. Signal processing is very important in this field for issues such as sending and receiving signals, coding, modulation and demodulation.
Image Processing: In this context, signals are analyzed as images in digital or analog form. This image information is commonly used for object recognition, medical imaging, satellite imaging and many other applications.
Sound processing: In the field of audio processing, signals are related to sounds and sound waves. This field includes applications such as audio recording, music playback, speech recognition, and sound wave analysis in music and medicine.
medical: In medicine, signal processing is used to analyze biomedical signals such as electroencephalography (EEG) signals, electrocardiography (ECG) signals, and medical imaging signals (MRI and CT scan).
Electrical and Electronic Engineering: In electrical and electronic engineering, signal processing is used in the design of electronic systems, filtering signals, object recognition and control systems.
Geological disciplines: In this context, signals are usually associated with geologic measurements and measurements such as seismology and geologic data analysis.
Also, signal processing as a science has common issues with other fields of engineering and applied sciences and can contribute to a large number of other fields. This field includes various techniques such as Fourier transforms, filtering, pattern recognition, and wavelet analysis and is of great importance in the scientific and industrial communities.