Systems, Signal Processing and Digital Signal Processing

Systems, Signal Processing and Digital Signal Processing

Systems is any process that produces an output signal in response to an input signal. Continuous systems input and output continuous signals, such as in analog electronics. Discrete systems input and output discrete signals, such as computer programs that manipulate the values stored in arrays.

Signal processing is an enabling technology that encompasses the fundamental theory, applications, algorithms, and implementations of processing or transferring information contained in many different physical, symbolic, or abstract formats broadly designated as signals. It uses mathematical, statistical, computational, heuristic, and linguistic representations, formalisms, and techniques for representation, modelling, analysis, synthesis, discovery, recovery, sensing, acquisition, extraction, learning, security, or forensics

Digital signal processing (DSP) is the use of digital processing, such as by computers, to perform a wide variety of signal processing operations. The signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency.

Digital signal processing and analog signal processing are subfields of signal processing. DSP applications include audio and speech signal processing, sonar, radar and other sensor array processing, spectral estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control of systems, biomedical engineering, seismic data processing, among others.

Digital signal processing can involve linear or nonlinear operations. Nonlinear signal processing is closely related to nonlinear system identification  and can be implemented in the time, frequency, and spatio-temporal domains.

The application of digital computation to signal processing allows for many advantages over analog processing in many applications, such as error detection and correction in transmission as well as data compression.  DSP is applicable to both streaming data and static (stored) data.

Electrical Engineering course suggestions (advised to take more classes in the area that are not listed):

EEE3308C- Electronic Circuits 1

EEE4511C- Application of DSP

EEE4306- Electronic Circuits 2

EEE4310-Digital Integrated Circuits

EEL4930- Machine Learning

EEL3402- Remote Sensing

EEL4514C- Communications Systems

EEL4657C- Linear Controls

Skill Sets/Non-Engineering course suggestions:

Numerical Analysis courses: MAD4401, COT4501, or EGM3344

Probability and Statistics courses  

Strong Programming skills (MATLAB, C/C++ and PYTHON)

Algorithm Design type courses (COP3530)