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Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. 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 ...
Digital signal processing (DSP) algorithms typically require a large number of mathematical operations to be performed quickly and repeatedly on a series of data samples. Signals (perhaps from audio or video sensors) are constantly converted from analog to digital, manipulated digitally, and then converted back to analog form.
Digital signal processing is the processing of digitized discrete-time sampled signals. Processing is done by general-purpose computers or by digital circuits such as ASICs , field-programmable gate arrays or specialized digital signal processors .
Digital signal processing, the mathematical manipulation of an information signal; Digital signal processor, a microprocessor designed for digital signal processing; Dynamic Reconfiguration port; Yamaha DSP-1, a proprietary digital signal processor; Demand-side platform, a system to facilitate the buying of online advertising
Multidimensional Digital Signal Processing (MDSP) refers to the extension of Digital signal processing (DSP) techniques to signals that vary in more than one dimension. . While conventional DSP typically deals with one-dimensional data, such as time-varying audio signals, MDSP involves processing signals in two or more dimens
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In the context of digital signal processing (DSP), a digital signal is a discrete time, quantized amplitude signal. In other words, it is a sampled signal consisting of samples that take on values from a discrete set (a countable set that can be mapped one-to-one to a subset of integers ).
In digital signal processing (DSP), a normalized frequency is a ratio of a variable frequency and a constant frequency associated with a system (such as a sampling rate, ). Some software applications require normalized inputs and produce normalized outputs, which can be re-scaled to physical units when necessary.