Signal processing is a branch of engineering and mathematics that involves the analysis, manipulation, and transformation of signals or data to extract meaningful information or enhance their quality for various applications. It encompasses a broad range of techniques and methods used to process both analog and digital signals.
In signal processing, a signal refers to any quantity that carries information and can be represented as a function of one or more independent variables, such as time, space, or frequency. Signals can originate from various sources, including audio, video, radio, biomedical, and many others.
The main goal of signal processing is to extract meaningful information or features from signals, remove unwanted noise or distortions, or transform signals into a more suitable format for further analysis or storage. This process usually involves steps like data acquisition, pre-processing, feature extraction, signal modeling, filtering, compression, and interpretation.
Signal processing techniques can be categorized into two main domains: analog and digital signal processing. Analog signal processing mainly deals with continuous-time signals, while digital signal processing focuses on discrete-time signals that are represented using binary numbers. Digital signal processing often involves the use of algorithms and computers to process signals efficiently.
Signal processing finds extensive applications in fields such as telecommunications, image and video processing, audio processing, speech recognition, radar and sonar systems, medical imaging, sensor networks, and many more. It plays a crucial role in improving the quality, efficiency, and reliability of information transmission and analysis in numerous real-world applications.
