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While conventional DSP typically deals with one-dimensional data, such as time-varying audio signals, MDSP involves processing signals in two or more dimensions. Many of the principles from one-dimensional DSP, such as Fourier transforms and filter design, have analogous counterparts in multidimensional signal processing.
The Goertzel algorithm is a technique in digital signal processing (DSP) for efficient evaluation of the individual terms of the discrete Fourier transform (DFT). It is useful in certain practical applications, such as recognition of dual-tone multi-frequency signaling (DTMF) tones produced by the push buttons of the keypad of a traditional analog telephone.
The DSP implementation in the folding algorithm is a Data flow graph(DFG), which is a graph composed of functional nodes and delay edges.. Another input for folding algorithm is folding set which is the function maps an operation unit of original DFG to an operation of transformed DFG with the number n <= N indicated the order of reused operation.
The resulting output waveform is a staircase with step size , the integer value of the FCW. [6] In some configurations, the phase output is taken from the output of the register which introduces a one clock cycle latency but allows the adder to operate at a higher clock rate.
Sample-rate conversion, sampling-frequency conversion or resampling is the process of changing the sampling rate or sampling frequency of a discrete signal to obtain a new discrete representation of the underlying continuous signal. [1]
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. [1] [2] Unfolding in general program is as known as Loop unrolling.
In digital signal processing (DSP), parallel processing is a technique duplicating function units to operate different tasks (signals) simultaneously. [1] Accordingly, we can perform the same processing for different signals on the corresponding duplicated function units.
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.