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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 ...
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
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.
In digital signal processing, downsampling, compression, and decimation are terms associated with the process of resampling in a multi-rate digital signal processing system. Both downsampling and decimation can be synonymous with compression , or they can describe an entire process of bandwidth reduction ( filtering ) and sample-rate reduction.
Unfolding is a transformation technique of duplicating the functional blocks to increase the throughput of the DSP program in such a way that preserves its functional behavior at its outputs. Unfolding was first proposed by Keshab K. Parhi and David G. Messerschmitt in 1989.
Pipelining is an important technique used in several applications such as digital signal processing (DSP) systems, microprocessors, etc. It originates from the idea of a water pipe with continuous water sent in without waiting for the water in the pipe to come out. Accordingly, it results in speed enhancement for the critical path in most DSP ...
When working with digital audio, digital signal processing (DSP) techniques are commonly used to implement compression as audio plug-ins, in mixing consoles, and in digital audio workstations. Often the algorithms are used to emulate the above analog technologies. [citation needed]
This large complexity generally results in an extremely long execution run-time of a given mD-DSP application rendering its usage to become impractical for many applications; especially for real-time applications. [3] This long run-time is the primary motivation of applying parallel algorithmic techniques to mD-DSP problems.