Digital signal processing
The digital 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.
Theoretical DSP analyses and derivations are typically performed on discrete-time signal models with no amplitude inaccuracies (quantization error), created by the abstract process of sampling.
Similarly, space domain refers to the analysis of signals with respect to position, e.g., pixel location for the case of image processing.
The most common processing approach in the time or space domain is enhancement of the input signal through a method called filtering.
The Fourier transform converts the time or space information to a magnitude and phase component of each frequency.
Where phase is unimportant, often the Fourier transform is converted to the power spectrum, which is the magnitude of each frequency component squared.
The engineer can study the spectrum to determine which frequencies are present in the input signal and which are missing.
The Z-transform provides a tool for analyzing stability issues of digital IIR filters.
This method has higher frequency resolution and can process shorter signals compared to the Fourier transform.
Temporal and frequency resolution are limited by the principle of uncertainty and the tradeoff is adjusted by the width of analysis window.
Non-linear and segmented Prony methods can provide higher resolution, but may produce undesirable artifacts.
For example, methods of fundamental frequency estimation, such as RAPT and PEFAC[14] are based on windowed spectral analysis.
[18] Additional technologies for digital signal processing include more powerful general-purpose microprocessors, graphics processing units, field-programmable gate arrays (FPGAs), digital signal controllers (mostly for industrial applications such as motor control), and stream processors.
Others, such as Pro Tools HD, Universal Audio's UAD-1 and TC Electronic's Powercore use DSP processing.
General application areas for DSP include Specific examples include speech coding and transmission in digital mobile phones, room correction of sound in hi-fi and sound reinforcement applications, analysis and control of industrial processes, medical imaging such as CAT scans and MRI, audio crossovers and equalization, digital synthesizers, and audio effects units.
[22] DSP has been used in hearing aid technology since 1996, which allows for automatic directional microphones, complex digital noise reduction, and improved adjustment of the frequency response.
