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Unfolding has applications in designing high-speed and low-power ASIC architectures. One application is to unfold the program to reveal hidden concurrency so that the program can be scheduled to a smaller iteration period, thus increasing the throughput of the implementation. Another application is parallel processing in word level or bit level.
A makeshift to achieve a real-time requirement in multidimensional DSP applications is to use a lower sampling rate, which can efficiently reduce the number of samples to be processed at one time and thereby decrease the total processing time. However, this can lead to the aliasing problem due to the sampling theorem and poor-quality outputs ...
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 ...
Many DSP applications have constraints on latency; that is, for the system to work, the DSP operation must be completed within some fixed time, and deferred (or batch) processing is not viable. Most general-purpose microprocessors and operating systems can execute DSP algorithms successfully, but are not suitable for use in portable devices ...
Then, the output sample y(n) can be computed in terms of the inputs and the output sample y(n − M) such that there are M delay elements in the critical loop. These elements are then used to pipeline the critical loop by M stages so that the sample rate can be increased by a factor M. Consider the 1st-order IIR filter transfer function
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.
Analog discrete-time signal processing is a technology based on electronic devices such as sample and hold circuits, analog time-division multiplexers, analog delay lines and analog feedback shift registers. This technology was a predecessor of digital signal processing (see below), and is still used in advanced processing of gigahertz signals. [7]
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 ).