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The following graph shows the example of folding transformation. The original DSP system produces y(n) at each unit time. The transformed DSP system produces y(n) in each 2 l where each 2 l increase 1 n, index of y. The resource used in original system are 2 adders, and the resource used in transformed system are 1 adder, 1 register, 3 multiplexer.
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 systems. For example, it can either increase the clock speed or reduce the power consumption at the same speed in a DSP system.
The following graph is another example showing the unfolding algorithm. Notice that, if there is the delay smaller than unfolding factor J , the J -unfolded DFG would create the edge with 0 delay but whose corresponding edge at original DFG may be the non-zero edge.
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An example of such an application is processing digital photographs with software such as Photoshop. When the application requirement is real-time, DSP is often implemented using specialized or dedicated processors or microprocessors, sometimes using multiple processors or multiple processing cores.
In order to maintain the same sample rate, the clock period of the N-parallel circuit increases to N times the propagation delay of the original circuit. It makes the charging time prolongs N times. The supply voltage can be reduced to βV 0. Therefore, the power consumption of the N-parallel system can be formulated as
A digital signal processor (DSP) is a specialized microprocessor chip, with its architecture optimized for the operational needs of digital signal processing. [ 1 ] : 104–107 [ 2 ] DSPs are fabricated on metal–oxide–semiconductor (MOS) integrated circuit chips.
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