Signal processing is an area of systems engineering, electrical engineering and applied mathematics that deals with operations on or analysis of signals, in either discrete or continuous time. Signals of interest can include sound, images, time-varying measurement values and sensor data, for example biological data such as electrocardiograms, control system signals, telecommunication transmission signals, and many others. Signals are analog or digital electrical representations of time-varying or spatial-varying physical quantities.

Processing of signals includes the following operations and algorithms with application examples:

In communication systems, signal processing may occur at OSI layer 1, the Physical Layer (modulation, equalization, multiplexing, etc.) in the seven layer OSI model, as well as at OSI layer 6, the Presentation Layer (source coding, including analog-to-digital conversion and data compression).

According to Alan V. Oppenheim and Ronald W. Schafer, the principles of signal processing can be found in the classical numerical analysis techniques of the 17th century. They further state that the "digitalization" or digital refinement of these techniques can be found in the digital control systems of the 1940s and 1950s.

Information theory is a branch of applied mathematics and electrical engineering involving the quantification of information. Information theory was developed by Claude E. Shannon to find fundamental limits on signal processing operations such as compressing data and on reliably storing and communicating data. Since its inception it has broadened to find applications in many other areas, including statistical inference, natural language processing, cryptography generally, networks other than communication networks — as in neurobiology, the evolution and function of molecular codes, model selection in ecology, thermal physics,quantum computing, plagiarism detection and other forms of data analysis.

A key measure of information is known as entropy, which is usually expressed by the average number of bits needed to store or communicate one symbol in a message. Entropy quantifies the uncertainty involved in predicting the value of a random variable. For example, specifying the outcome of a fair coin flip (two equally likely outcomes) provides less information (lower entropy) than specifying the outcome from a roll of a die (six equally likely outcomes).

Adam Schneider (born 12 May 1984) is an Australian rules footballer playing for the St Kilda Football Club in the Australian Football League (AFL). Schneider formerly played for the Sydney Swans.

Originally from the small town of Osbourne, Schneider spent most of his teenage years at St Francis De Sales Regional College in Leeton, then Kooringal High And Trinity High School in Wagga Wagga where he decided to pursue Australian rules football after also excelling in cricket.^{[citation needed]}

Schneider was recruited from Osbourne and NSW-ACT U18 by Sydney Swans in the 2001 AFL Draft. He was Sydney's 4th Round selection and number 60 overall.

During his first season at the club, Schneider suffered minor injuries and illness which sidelined him for over three months.

However, in 2003, Schneider hit the ground running. Through the pre-season and practice matches he was in great form and earned his senior AFL debut. He debuted in Round 1 of the 2003 premiership season against Carlton. His form was good enough for him to hold his place in the seniors for all 24 matches as well as kicking 30 goals for the season.